Multi-criteria Decision Analysis infrastructure

The application of multiattribute decision analysis to personal consequential decision problems can be unhelpful particularly where the analysis fails to help the decision maker to discover new values, or where the decision maker is unable to visualize the experience that may result from choosing a particular course of action. We concur with James March that values are best discovered by the act of choosing and experimenting but acknowledge that the act of choice can lead to irreversible consequences. Both of these problems suggest that techniques which assist the decision maker to envisage the consequences of choice need to be developed and incorporated into the modelling process. We suggest some forms that these techniques might take.

Created by the State Department's Office of the Coordinator for Reconstruction and Stabilization, the Civilian Response Corps (CRC) contains a diverse pool of qualified and ready-to-deploy civilian professionals that support conflict prevention and response efforts in countries or regions that are at risk of, are currently in, or are transitioning from conflict or civil strife. As such, it is vital to optimize the CRC's skill groupings to maximize adaptability and responsiveness to highly uncertain and trying political conditions and crises across the globe. The nature of the CRC value proposition is such that determining which skill set compositions deliver the greatest benefit requires a multi-faceted perspective that looks at a number of attributes and factors, both tangible and intangible. To meet these needs, an organizational decision-making approach utilizing multi-criteria decision analysis (MCDA) was applied to ensure that skill-grouping allocations were determined in a logical and robust manner. The MCDA analysis allowed for a wide range of worldviews and perspectives, drawn from select members of academia and partner agencies of the CRC who provided their expert opinions on the expected demand for skill groupings commonly identified as most necessary in a civilian 'surge' capacity. These skills were assessed with reference to a values hierarchy of representative country scenarios, missions and sub-missions identified by the Office of the Coordinator for Reconstruction and Stabilization. Of particular interest was the use of the MCDA method to prioritize CRC skill groupings and to help inform the Department of State's understanding of the 'ideal' proportion and types of civilian skills for inclusion in the CRC.

We propose a log-based analysis tool for evaluating web application computer system. A feature of the tool is an integration software log with infrastructure log. Software engineers alone can resolve system faults in the tool, even if the faults are complicated by both software problems and infrastructure problems. The tool consists of 5 steps: preparation software, preparation infrastructure, collecting logs, replaying the log data, and tracing the log data. The tool was applied to a simple web application system in a small-scale local area network. We confirmed usefulness of the tool when a software engineer detects faults of the system failures such as " 404 " and " no response " errors. In addition, the tool was partially applied to a real large-scale computer system with many web applications and large network environment. Using the replaying and the tracing in the tool, we found causes of a real authentication error. The causes were combined an infrastructure problem with a software problem. Even if the failure is caused by not only a software problem but also an infrastructure problem, we confirmed that software engineers alone could distinguish between a software problem and an infrastructure problem using the tool.

This paper outlines the approach to the evaluation of sustainability of current and future electricity supply options of interest for a major Swiss utility Axpo Holding AG. The motivation behind this effort has been to provide a solid basis for a state-of-the-art interdisciplinary assessment and use this framework within a dialog with a wide spectrum of stakeholders. The development and implementation of the methodology was coordinated by Axpo in co-operation with the Paul Scherrer Institut (PSI) and other scientific institutions.

Inter-organizational Global Software Development (GSD) has become a common reality for many projects. It is well established that distance makes difficult to interact and to cooperate effectively. Scrum, a consolidated Agile methodology, emphasizes communication, reduces coordination and control overhead and has been increasingly used in a distributed fashion. Successfully planning and managing the combined use of GSD and Scrum is a complex task and requires carefully planning. Despite the importance and complexity of this type of problem, there seems to be a lack of reports, in the literature, of models that could support managers dealing with these decision contexts. This paper presents a multi-criteria decision model for planning and fine-tuning such project plans. This model was developed using cognitive mapping and MACBETH[1]. The application of the model is demonstrated, followed by conclusion and future work.

Selection of new geographies in which to expand is a key decision for businesses aspiring to go beyond the opportunities in the existing markets. The conventional approaches of market selection can only provide a set of systematic steps for problem solving without considering the relationships between the decision factors. Decision models based on statistical techniques are able to examine the relationship between decision factors but are unable to effectively assist decision makers in identifying the most promising market, particularly in terms of prioritizing across decision factors. Analytic Hierarchy Process (AHP) is a commonly used approach for choosing alternatives by prioritizing across multiple decision factors. The typical AHP modelling requires knowledge of criteria and/or alternatives along with their relative weights, generally elicited from field experts. Quite often, firms encounter situations where decision makers are aware of only the overall objective and a set of earmarked geographies for setting up market locations while being relatively unaware of decision criteria and relative weights. This precludes using AHP to identify promising market locations. This paper conceptualizes a market selection decision model that integrates AHP with statistical modelling techniques to identify the attractive market locations for the purpose of expansion. The model first uses principal component analysis and multiple regression to determine significant decision criteria and their weights. Thereafter, it applies AHP to prioritize the market locations across the decision criteria. This integrative approach is illustrated for identifying the attractive locations in rural markets for a steel firm in India. The major advantage of this approach is that unlike the existing models, it works in situations when firms have not enough knowledge about factors for evaluating alternative market locations. Another key advantage of the proposed model is that of economizing resources for data collection on variables representing decision factors.

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis does not provide an analytical means to determine the importance of the identified factors or the ability to assess decision alternatives according to these factors. Although the analysis successfully pinpoints the factors, individual factors are usually described briefly and very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation steps. Although the analytic hierarchy process (AHP) technique removes these deficiencies, it does not allow for measurement of the possible dependencies among the factors. The AHP method assumes that the factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain internal and external environmental effects. Therefore, it is necessary to employ a form of SWOT analysis that measures and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the strategic factors, as well as AHP, which is based on the independence between the factors. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities. .tr (M. Daǧdeviren). Information Sciences 177 (2007) 3364-3382 www.elsevier.com/locate/ins _ I. Yü ksel, M. Daǧ deviren / Information Sciences 177 (2007) 3364-3382

Multi-criteria analysis of remediation alternatives to access their overall impact and cost/benefit, with focus on soil function (ecosystem services and goods) and sustainability Final Report of the SNOWMAN-MCA project carried out as part of the SNOWMAN Network coordinated call II

Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the lastest research advances in this field.

Most commonly, sustainability indicator sets presented as lists do not take into account interactions among indicators in a systematic manner. Vice versa, existing environmental indicator systems do not provide a formalized approach for problem structuring and quantitative decision support. In this paper, techniques for considering indicator relationships are highlighted and a coupled approach between a qualitative and a quantitative method is analysed. Cognitive mapping (CM) is used for structuring indicators and three different causal maps are derived based on established sustainability concepts: (a) criteria and indicators (C&I hierarchy), (b) indicator network, and (c) Driving Force-Pressure-State-Impact-Response (DPSIR) system. These maps are transferred to the Analytic Network Process (ANP) to allow their application in multi-criteria decision analysis (MCDA).

So far, competing forecasting models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria -a situation where one cannot make an informed decision as to which model performs best overall; that is, taking all performance criteria into account. To overcome this methodological problem, we propose to use a Multi-Criteria Decision Analysis (MCDA) based framework and discuss how one might adapt it to address the problem of relative performance evaluation of competing forecasting models. Three outranking methods have been used in our empirical experiments to rank order competing forecasting models of crude oil prices; namely, ELECTRE III, PROM-ETHEE I, and PROMETHEE II. Our empirical results reveal that the multidimensional framework provides a valuable tool to apprehend the true nature of the relative performance of competing forecasting models. In addition, as far as the evaluation of the relative performance of the forecasting models considered in this study is concerned, the rankings of the best and the worst performing models do not seem to be sensitive to the choice of importance weights or outranking methods, which suggest that the ranks of these models are robust.

In this paper a collective choice function (CCF), formulated within a p-metric distance function framework, is proposed as a generator of several compromise consensuses. Even though, the proposed CCF is not smooth, it is however demonstrated that it can be straightforwardly transformed into easily computable goal programming models. Finally, several cases of individual preferences aggregation are obtained by providing different interpretations of the CCF parameters: ordinal and complete information, ordinal and partial information and a cardinal case through 'pairwise' comparison matrices.

Several Multi-Criteria Decision Analysis (MCDA) models for use in health technology assessment (HTA) have been developed over the years, including some for orphan drugs. However, there is no general consensus yet on MCDA structure and which criteria should be included and implementation of MCDA into HTA practice has been slow so far. Our study tested the criteria preferences and possibilities for implementation of the EVIDEM MCDA framework for orphan drugs with a diverse group of 140 stakeholders in Kazakhstan, Netherlands, Poland, Romania, Russia, Turkey and Ukraine (KZ, NL, PL, RO, RU, TR, UA). The research elicited stakeholder preferences (weighting) for EVIDEM domains, criteria and sub-criteria to measure their relative importance. Correlations of the workplace and HTA/rare diseases experience with weighting results were investigated.

The vital importance of a reliable and safe drinking water supply makes efficient risk management necessary for water utilities. Risks must be assessed and possible risk-reduction measures evaluated to provide relevant decision support. The World Health Organization emphasises the use of an integrated approach where the entire drinking water system, from source to tap, is considered when assessing and managing risks. Integrated risk assessments are important in order to avoid overlooking interactions between subsystems and events and to minimise sub-optimisation of risk-reduction measures. Methods for integrated risk assessment are, however, limited. A dynamic fault tree method is presented that enables quantitative, integrated risk assessment of drinking water systems. An approach for approximate dynamic fault tree calculations has been developed to minimise computational demand. It is shown how the method can be used to evaluate uncertainties and provide information on risk levels, failure probabilities, failure rates and downtimes of the entire system and its subsystems. The fault tree method identifies where risk-reduction measures are needed most and different risk-reduction alternatives can be modelled, evaluated and compared. The method is combined with economic analysis to identify the most cost-effective risk-reduction alternative. Integrated risk assessments of drinking water systems are commonly performed using risk ranking, where the probability and consequence of undesired events are assessed using discretised scales. There is, however, no common, structured way of using risk ranking to prioritise riskreduction measures. Two alternative models for risk-based, multi-criteria decision analysis (MCDA) for evaluating and comparing risk-reduction measures have therefore been developed. The MCDA models are based on risk ranking, they can consider uncertainty in estimates and include criteria related to, for example, different risk types and economic aspects. In summary, this thesis provides methods for integrated risk assessment that make it possible to prioritise risk-reduction measures. It is concluded that the methods provide relevant decision support for efficient risk management in water utilities.

Control Benchmarking Multi-criteria decision analysis Uncertainty Monte Carlo simulation a b s t r a c t The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success. (I. Rodríguez-Roda), gsi@kt.dtu.dk (G. Sin), kvg@kt.dtu.dk (K.V. Gernaey).

ABSTRACT Supported by a network of researchers and practitioners, the goal programming (GP) model is alive today more than ever and is continually fed with theoretical developments and new applications with resounding success. The standard formulation of the GP model was introduced in the earliest of 1960s, and since then, important extensions and numerous applications have been proposed. One of these variants is the stochastic GP model that deals with the uncertainty of some decision‐making situations by using stochastic calculus. In such a situation, the decision maker is not able to assess with certainty the different parameters. However, he or she can provide some information regarding the likelihood of occurrence of the decision‐making parameter values. The aim of this paper is to highlight the main methodological developments of the stochastic GP model and to present an overview of its applications in several domains. Copyright © 2012 John Wiley & Sons, Ltd.

Grass biogas/biomethane has been put forward as a renewable energy solution and it has been shown to perform well in terms of energy balance, greenhouse gas emissions and policy constraints. Biofuel and energy crop solutions are country-specific and grass biomethane has strong potential in countries with temperate climates and a high proportion of grassland, such as Ireland. For a grass biomethane industry to develop in a country, suitable regions (i.e. those with the highest potential) must be identified. In this paper, factors specifically related to the assessment of the potential of a grass biogas/biomethane industry are identified and analysed. The potential for grass biogas and grass biomethane is determined on a county-by-county basis using multi-criteria decision analysis. Values are assigned to each county and ratings and weightings applied to determine the overall county potential. The potential for grass biomethane with co-digestion of slaughter waste (belly grass) is also determined. The county with the highest potential (Limerick) is analysed in detail and is shown to have ready potential for production of gaseous biofuel to meet either 50% of the vehicle fleet or 130% of the domestic natural gas demand, through 25 facilities at a scale of ca. 30 kt yr−1 of feedstock. The assessment factors developed in this paper can be used in other resource studies into grass biomethane or other energy crops.► We identified assessment criteria for determining the regional potential for grass biomethane. ► Grass biomethane is distributed via the natural gas grid. ► The criteria include: land use; grass yields; gas grid coverage; availability of co-substrates. ► The county with the highest potential can fuel 50% of cars or supply 130% of domestic gas consumption.

Use of online matrimony for matchmaking is rapidly growing in India. One of the major difficulties faced by the users of such websites is the long time taken to realize the matches. We propose an integrated approach to matchmaking in e-matrimony environment using fuzzy analytical hierarchy process considering multiple criteria involved in the process. The objective of the study is to enable users to search their partners effectively and efficiently and narrow down to the desired matches so that the chances of matchmaking through online portal are maximized. A compatibility index, that is match metric, is developed that enhances the probability of matchmaking with reduction in lead time. Furthermore, Gale-Shapley stable matching algorithm is used to help customers obtain the desired shortlist of profiles with a suggested stable match. An illustrated hypothetical example of matchmaking using an Indian matrimony portal is presented, and the use of the proposed methodology is demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.

The topic of ‘how mega transport projects should be assessed’ continues to generate disputes amongst academics, infrastructure specialists, investors and governments alike. This Ph.D. research sought to explore the applicability of participatory MCA methodologies to the (economic, environmental and social) appraisal of such projects. Although very popular amongst academics, participatory MCA techniques seem to have enjoyed limited practical application and there are no studies assessing their effectiveness. This research entailed several steps, where different methods of investigation and multiple sources of information, both primary and secondary, were combined together in an effort to increase the reliability of the results. Firstly, a comprehensive review of the literature, whose findings were validated and integrated by means of an expert focus group interview, was undertaken in the attempt to determine the key features of mega transport projects. An investigation into transport appraisal practice and traditional appraisal methodologies was then carried out through a comprehensive analysis of the existing literature, complemented with unstructured interviews and informal discussions with some international experts. Successively, an examination of over 60 publications on participatory MCA methodologies was performed with the objective of determining the main attributes and critical aspects of such methods. An analysis of the current trends in mega transport infrastructure planning and decision-making practice was also undertaken based on a series of interviews with several infrastructure practitioners and the analysis of three large-scale port and port-related projects, namely the Alameda freight rail corridor (US), the expansion of the Port of Rotterdam (Holland) and the London Gateway port complex (UK). The London Gateway port complex was also adopted as case study for a practical application of participatory MCA methodologies. Overall, the outcomes of this multi-actor multi-criteria appraisal exercise, together with the findings from the previous steps of research, led to the identification of several (methodological and non-methodological) issues potentially surrounding the practical application of such methods. These issues were ultimately explored through a survey questionnaire carried out amongst specialists and proponents of participatory techniques. The overall conclusion of the thesis is that participatory MCA methodologies represent an under-researched area, where some critical themes have received limited consideration; contrasting views still exist on many fundamental aspects; and where, in many cases, the disconnection between theory and practice is apparent. In particular, the key principles, steps and structure of such methods are (directly or indirectly) based on the rational-comprehensive planning model, which hardly reflects the way projects are developed. Therefore, while, in principle, multi-actor multi-criteria procedures might be carried out to complement and integrate the information derived from conventional ex-ante analyses, it is difficult to see how such methods could significantly improve the decision-making process of major transport infrastructure.

Multi-criteria analysis (MCA), in the literature also known under the names of multiple-criteria decision-making (MCDM), multiple-criteria decision analysis (MCDA), multi-objective decision analysis (MODA), multiple-attribute decision-making (MADM) or multi-dimensional decision-making (MDDM), comprises various classes of methods, techniques and tools, with different degrees of complexity, that explicitly consider multiple objectives and criteria (or attributes) in decision-making problems. Since the late 20th century, MCA methods have ignited an increasing interest amongst researchers and practitioners working in a number of fields.
Whereas a number of articles, books and manuals have been written on the subject, the large majority of these are either too technical or overly simplistic. The former type of publications, on the one hand, is hardly readable and comprehensible for non-specialists. The latter pieces of work, on the other hand, tend to ignore many critical aspects of MCA and contribute to the diffusion of practices that are fundamentally flawed. This paper represents an attempt to find a middle ground between those two positions. Its main purpose is to help students, academics, but also practitioners and all those approaching this field of knowledge for the first time to gain insight into the key features of MCA with the view to enabling them to access more complex textbooks in the future. The paper also offers practical guidance regarding the fundamental tasks required to develop basic, yet rigorous multi-criteria frameworks and effectively apply them to different types of decision-making situations and problems. This constitutes the first foundational step for eventually mastering more rigorous and elaborated MCA techniques. Finally, this paper also seeks to discuss the potential advantages and limitations of MCA by adopting, as far as possible, a balanced and neutral perspective so as to break down clichés and false beliefs on the subject.

In the 21st century, adequate and reliable infrastructure for a country is essential for sustainable development and improving competitiveness in a world influenced by globalization. Indonesia is a country that still requires a significant increase in infrastructure development. To build infrastructures, however, it will also require substantial investment in a sustainable financing system. Financing decisions are not neceesarily equivalent to investment decisions and they can be independently decided. Research focusing on the available options for infrastructure financing is an essential component of the infrastructure development process. The main sources of infrastructure financing include public budgets, budget appropriations, financing on a pay-as-you-go basis or from public debt. These options persist as the major form of financing for government investment in infrastructure. However, recent Public Private Partnership (PPP) procurement through financing from equity capital and lending from banks, and infrastructure bonds, has become an attractive alternative source for infrastructure financing. Infrastructure financing has multiple consequences; therefore, governments and related stakeholders have to consider a range of macro and micro economic factors when undertaking project appraisal and comparisons. Project risk can be reduced by appropriate project management. However, operation and maintenance costs need to be included to manage the effectiveness of revenue and costing in a holistic manner. To avoid unnecessary complexity in the negotiation between the public and private sectors, standardised project agreements and contracts can be introduced. PPP infrastructure projects should be well prepared and run to increase the confidence of public and private parties throughout the PPP process. Therefore, the use of a more consistent and transparent risk allocation framework aligned with published guidance material would accelerate the process of negotiation around risk allocation and distribution. The major financing task is to meet upfront investment costs in a timely manner whilst the central efficiency issue is in deciding which financing vehicle best manages project risk. In light of the ongoing discussion, a research was set to develop robust frameworks to assess the investment decision for infrastructure projects within the PPP financing mechanism

Although additive layer manufacturing is well established for rapid prototyping the low throughput and historic costs have prevented mass-scale adoption. The recent development of the RepRap, an open source self-replicating rapid prototyper, has made low-cost 3-D printers readily available to the public at reasonable prices (<$1,000). The RepRap (Prusa Mendell variant) currently prints 3-D objects in a 200x200x140 square millimeters build envelope from acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA). ABS and PLA are both thermoplastics that can be injection-molded, each with their own benefits, as ABS is rigid and durable, while PLA is plant-based and can be recycled and composted. The melting temperature of ABS and PLA enable use in low-cost 3-D printers, as these temperature are low enough to use in melt extrusion in the home, while high enough for prints to retain their shape at average use temperatures. Using 3-D printers to manufacture provides the ability to both change the fill composition by printing voids and fabricate shapes that are impossible to make using tradition methods like injection molding. This allows more complicated shapes to be created while using less material, which could reduce environmental impact.

As the open source 3-D printers continue to evolve and improve in both cost and performance, the potential for economically-viable distributed manufacturing of products increases. Thus, products and components could be customized and printed on-site by individual consumers as needed, reversing the historical trend towards centrally mass-manufactured and shipped products. Distributed manufacturing reduces embodied transportation energy from the distribution of conventional centralized manufacturing, but questions remain concerning the potential for increases in the overall embodied energy of the manufacturing due to reduction in scale. In order to quantify the environmental impact of distributed manufacturing using 3-D printers, a life cycle analysis was performed on a plastic juicer. The energy consumed and emissions produced from conventional large-scale production overseas are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA are discussed in relation to the environmental impact of distributed manufacturing with 3-D printers and polymer selection for 3-D printing to reduce this impact. The results of this study show that distributed manufacturing uses less energy than conventional manufacturing due to the RepRap's unique ability to reduce fill composition. Distributed manufacturing also has less emissions than conventional manufacturing when using PLA and when using ABS with solar photovoltaic power. The results of this study indicate that open-source additive layer distributed manufacturing is both technically viable and beneficial from an ecological perspective.

The financial inclusion is a crucial element in the fight against poverty. The ability to take effective decisions regarding the use and management of money with required informed judgments is financial literacy. It enables a person to understand the importance of savings and thus regarded as an important requirement for functioning effectively in modern society. Large sections of the rural population borrow from moneylenders (their sole resource) at a very high and unreasonable cost causing slavery and have no access to any financial services. The article highlights that considering the immensely large population of the country, the progress on financial inclusion is not enough and financial institutions and banks need to manage their efforts towards financial inclusion since the development of the economy is impacted and linked with the extent of financial inclusion in the country. Access to finance by the underprivileged group, poor, and disadvantaged is essential to remove poverty on one hand and the economic growth on the other.

This report’s main aim is to propose a methodology for assessing state-budget-funded projects based on a rigorous selection model, including clear and effective prioritization criteria. This report first argues that project prioritization and selection should be optimized against four dimensions: absorption, impact, legitimacy, and capacity. Second, it provides a diagnostic of the National Program for Local Development (PNDL), managed by the Ministry of Regional Development and Public Administration (MRDPA), as the most significant source of state-budget funding for local infrastructure projects. The PNDL’s current design and implementation leaves room for improvement, as reflected by the lack of strategic direction in allocating funds and the continued rise in the number of projects that get started without a feasible timeline for their completion. Further, this report makes recommendations for improvement of project evaluation and selection procedures for local infrastructure development projects, with a special focus on prioritization criteria and viable funding sources for each type of investment. The practical purpose is to enhance the efficiency and effectiveness of proposed investments, maximizing impact in the context of inherently limited available financial resources. A complementary focus is on opportunities for harmonizing and better coordinating investments across various sources of funding, in the context of nearly EUR 40 billion available to Romania from the EU for the 2014-2020 programming period.

In Greece Sanitary landfilling is the most common way of disposing of municipal solid wastes. However, one of the major problems in waste management now a days concerns is the selection procedure of the most appropriate site for their final disposal. In this paper a two-stage, multicriteria evaluation is presented. In the fist stage, in order to establish the promising sites, waste disposal is merely based on geotechnical criteria as it touches upon issues of the geoenvironment and the landscape as well as the suitability of geoenvironment for siting is depending mainly on its stability and on the danger of groundwater pollution. In the second stage these sites are evaluated using economic efficiency, environmental and technical economic criteria. It is interesting that the method sets the factors clearly and helps experts and local communities to participate. The method was easily applicable to a new landfill site selection in Northern Evoia and the results were accepted by the local communities.

In order to solve a number of real decision-making problems, over time, a number of multiple criteria decision-making methods have been proposed. The EDAS method is one of the newly proposed methods; its computational procedure can be identified as innovative and also based on verified approaches. An extension of the EDAS method adapted for the use of grey numbers is considered in this paper.

Decision analysis can be defined as a set of systematic procedures for analysing complex decision problems. Differences between the desired and the actual state of real world geographical system is a spatial decision problem, which can be approached systematically by means of multi-criteria decision making. Many real-world spatially related problems give rise to geographical information system based multi-criteria decision making. Geographical information systems and multi-criteria decision making have developed largely independently, but a trend towards the exploration of their synergies is now emerging. This paper discusses the synergistic role of multi-criteria decisions in geographical information systems and the use of geographical information systems in multi-attribute decision analysis. An example is provided of analysis of land use suitability by use of either weighted linear combination methods or ordered weighting averages.

Abstract: Landfill selection in an urban area is a critical issue in the urban planning process because of its enormous impact on the economy, ecology and the environmental health of the region. With the growth of urbanization as well as the desire to live in cities, lager ...

A spatial decision support system (SDSS) based on multi-criteria and multi-objective decision analysis is applied in a case study in Ethiopia to reduce soil erosion on the basis of reallocation of crops according to their capacity to protect the soil. The case study is carried out in the Adwa district. The SDSS has been implemented using the widespread GIS software IDRISI 32 (release 2) and with the direct involvement of local stakeholders in defining factors and constraints. These are based on land cover-land use, altitude, potential erosion, proximity to roads, water and the relative soil protective capacity of each crop species. A reduction of soil loss from an average of 4.5 t ha−1 yr−1 to values below the risk threshold of soil degradation (1 t ha−1 yr−1) would be achieved through the application of the SDSS results. The biggest impediment to the reallocation exercise, however, is the shortage of cultivable land suitable for cultivation.

The present paper delineates a three-step algorithm for the analytic network process (ANP) structure design. When defining the decision goal and the alternative set, one can use the three-step algorithm proposed in this paper, first, to specify the decision criteria and, second, to outline the structure of the ANP problem. To ease the process of ANP structure design, we present two novel data structures: the multiple-effect tree and the multiple-criteria tree. The multiple-effect tree helps explore the apparent consequences of a given event or state—known in this paper as the decision alternatives—while the multiple-criteria tree is considered the missing link between the multiple-effect tree and the ANP structure. Employing the approach presented in this paper will help detect any mistakes in the ANP structure design. A numerical example is provided in the final section of the paper to better articulate the ideas.

The main goal of green supply chain management (GSCM) is to reduce the negative environmental impacts in all activities and stages of a supply chain. Evaluation of suppliers in a supply chain according to environmental criteria can help us to achieve this goal of GSCM. Since this evaluation usually comprises some alternatives and some criteria, green supplier selection (GSS) could be considered as a multi-criteria decision-making (MCDM) problem. To handle the uncertainty of information in an MCDM problem, the theory of fuzzy sets is an effective tool. Interval type-2 fuzzy sets (IT2FSs), which are characterized by an interval membership function, is very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on Weighted Aggregated Sum Product Assessment (WASPAS) method, is proposed to deal with multi-criteria group decision-making problems with IT2FSs. This approach is based on the operators of IT2FSs, some modifications in the classical WASPAS method and a new procedure for calculation of criteria weights. In the procedure of calculation of criteria weights, we combine the subjective weights expressed by decision-makers with objective weights resulted from an entropy method to obtain more realistic weights. To show the applicability of the proposed approach in the real-world MCDM problems, a green supplier selection problem is used. We perform a sensitivity analysis with different weights of criteria and different values of method's parameters to show the stability of the proposed approach. This analysis shows that combining the subjective and objective weights can help to increase the stability of the proposed approach with different weights of criteria. A comparison is also made between the results of the proposed approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well consistent with the other methods.

Intersections are critical places which experience high levels of accidents due to the availability of vehicle movements from different directions. Therefore, there is a need to understand the factors that significantly contribute to injuries at such places. These factors can fall under different dimensions in traffic safety such as environmental conditions, road user behavior, traffic police enforcement, road design and crash characteristics. The paper will analyze the factors related to crash characteristics and traffic signal operation that affect the likelihood of accident severity located at intersections. The data for intersection accidents in Abu Dhabi from 2013 to 2016 were used in this analysis. Ordinal logistic model was considered for the analysis to account for the ordinal nature of severity levels. Several diagnostics tests of the model were preformed such as parameters evaluation, overall model evaluation and prediction accuracy. For parameter evaluation, out of 11 independent variables, 6 were non-significant and dropped from the model. Most of the non-significant variables were related to the driver-at-fault details. The results of the final model showed an overall good fit based on a p-value of less than 0.05, as well as a good accuracy of prediction 84.8%. Finally, odds ratios were estimated to interpret the final results of the model.

Because of the possible harmful effects of construction equipment on the environment, evaluation of them can be considered as a helpful activity to move toward the sustainability in construction. This evaluation process could involve some alternatives and some criteria in a discrete decision space. In this study, a new hybrid multi-criteria decision-making (MCDM) approach is proposed to deal with this evaluation process in the fuzzy environment. We present fuzzy extensions of the SWARA (Step-wise Weight Assessment Ratio Analysis) and CRITIC (CRiteria Importance Through Intercriteria Correlation) methods for determining subjective and objective weights of criteria. Based on these extended methods and the fuzzy EDAS (Evaluation based on Distance from Average Solution) method, a new hybrid approach is proposed. In this approach, the subjective and objective criteria weights are combined to determine more justified weights for criteria. The proposed approach is applied to a case study of construction equipment evaluation with sustainability considerations. To examine the result of evaluation, a sensitivity analysis is performed based on varying criteria weights. A comparison is also made between the results of the proposed approach and some existing MCDM methods. These analyses show the stability and validity of the results and efficiency of the proposed approach.

In this paper we give an overview of the use of Multi-Criteria Decision Analysis (MCDA) for transport project appraisal. The aim of this review is to provide an outline of the increasing use of MCDA methods in the evaluation of transport projects. We investigate for which kind of transport decisions the MCDA methods are applied. The review consists of identifying the transport related subjects, the interconnected arising decision problems and the kind of representative MCDA method(s) used for transport project evaluations. This review allowed deriving a general frame for the evaluation of transport projects. One of the conclusions resulted in the importance of integrating stakeholders in the decision process not yet very common in the transport projects that were reviewed. The Multi-Actor Multi-Criteria Analysis (MAMCA) approach is suggested as a direction for further research. The MAMCA methodology has already proven its usefulness in several transport related decision problems enabling to involve the stakeholders explicitly in the decision process.

We applied marine spatial planning (MSP) to manage conflicts in a multi-use coastal area of Kenya. MSP involves several steps which were supported by using geographical information systems (GISs), multicriteria decision analysis (MCDA) and optimization. GIS was used in identifying overlapping coastal uses and mapping conflict hotspots. MCDA was used to incorporate the preferences of user groups and managers into a formal decision analysis procedure. Optimization was applied in generating optimal allocation alternatives to competing uses. Through this analysis three important objectives that build a foundation for future planning of Kenya's coastal waters were achieved: 1) engaging competing stakeholders; 2) illustrating how MSP can be adapted to aid decision-making in multi-use coastal regions; and 3) developing a draft coastal use allocation plan. The successful application of MSP to resolve conflicts in coastal regions depends on the level of stakeholder involvement, data availability and the existing knowledge base.

A key factor to attain success in any discipline, especially in a field which requires handling large amounts of information and knowledge, is decision making. Most real-world decision-making problems involve a great variety of factors and aspects that should be considered. Making decisions in such environments can often be a difficult operation to perform. For this reason, we need multi-criteria decision-making (MCDM) methods and techniques, which can assist us for dealing with such complex problems. The aim of this paper is to present a new COmbinative Distance-based ASsessment (CODAS) method to handle MCDM problems. To determine the desirability of an alternative, this method uses the Euclidean distance as the primary and the Taxicab distance as the secondary measure, and these distances are calculated according to the negative-ideal point. The alternative which has greater distances is more desirable in the CODAS method. Some numerical examples are used to illustrate the process of the proposed method. We also perform a comparative sensitivity analysis to examine the results of CODAS and compare it by some existing MCDM methods. These analyses show that the proposed method is efficient, and the results are stable.

Supply chain risk management research has mainly mistreated the important of sustainability issues. Moreover, there is little knowledge about sustainable management of risk and supply chain and the way they impose losses for firms. Risk management's duty in the supply chain is to identify, analyze, and provide solutions for accountability, control and monitor the risks in the economic and production cycle. This study aims to develop a framework for the sustainable supply chain risk management (SSCRM) evaluation. To this end, an integrated fuzzy multi-criteria decision-making (MCDM) approach is proposed based on the technique in order of preference by similarity to ideal solution (TOPSIS) and criteria importance through inter-criteria correlation (CRITIC) methods. The literature was reviewed and the potential criteria were identified. Through an expert panel the criteria were filtered. Seven main criteria and forty-four sub-criteria were developed for the final evaluation SSCRM framework. The most dominant sub-criteria in each group found to be as; machines & equipment risks, key supplier failures, demand fluctuations, government policy risks, IT security, economic issues, and lack of proper sewage infiltration. Besides, A2 (Nouri complex) found to be the best practitioner. The methodology is successfully implemented in a real case company. The detailed account of implications and limitations are presented as the concluding remarks.