Multiple Criteria Decision Making

When a ranking is obtained for a set of projects, the introduction of a new project, worse than the others, may sometimes perturb the ranking. This is called rank reversal, and happens in most Multi Criteria Decision Making models. The purpose of this paper is to demonstrate that a new method, based on Linear Programming, is immune to rank reversal, which is proved by analyzing the algorithm used to solve the problem. The paper also examines a situation that produces rank reversal when two or more projects have close or identical values.

Purpose -The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling. Design/methodology/approach -Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that the following three questions can be answered: "What kind of decision problems were paid most attention to?"; "Were the multiple criteria decision-making techniques prevalently adopted?"; and "What are the inadequacies of these approaches?" Findings -Based on the inadequacies, some improvements and possible future work are recommended, and a comprehensive resource allocation model is developed taking account of these factors. Finally, a new knowledge-based goal programming technique which integrates some operations of analytic hierarchy process is proposed to tackle the model intelligently. Originality/value -Higher education has faced the problem of budget cuts or constrained budgets for the past 30 years. Managing the process of the higher education system is, therefore, a crucial and urgent task for the decision makers of universities in order to improve their performance or competitiveness.

Several paradigms can be used to analyse multiple-criteria decision-making problems. Of these goal programming is probably the most widely used one, at least in management science. Goal programming seems lo offer considerable potential f o r application to multiple-criteria problems in farm planning. However, its applications in agricultural economics have been few and far between. Even these attempfs seem to suffer from some serious misconceptions. In this paper an effort is made to explain the structure of a goal programming model by deriving it from the familiar paradigm of linear programming. This is done to put the porential usefulness of goal programming and its relationship to linear programming in perspective, and to encourage further applications to multiple-criteria decisionmaking in farm planning.

We describe a project on the classification of publications in the field of multiple criteria decision making (MCDM). Problems in defining and demarcating this field and its literature are discussed. We present the chosen approach of a classification based on a keyword system and propose two ways of its usage. One is based on a printed form. The other approach utilizes a database which allows an interactive information retrieval.

This paper describes a case study that used and evaluated key aspects of a method developed for systematic reusable off-the-shelf software selection. The paper presents a summary of the common problems in reusable off-the-shelf software selection, describes the method used and provides details about the case study carried out. The case study indicated that the evaluated aspects of the method are feasible, improve the quality and efficiency of reusable software selection and the decision makers have more confidence in the evaluation results, compared to traditional approaches. Furthermore, the case study also showed that the choice of evaluation data analysis method can influence the evaluation results.

مقدمه

مبحث این درس در خصوص تصمیم گیری با معیارهای چندگانه است که به آن
  (MCDM
Multi Criteria Decision Making)
می گویند
تصمیم گیری با معیارهای چندگانه دارای دو زیر شاخه اصلی  است
1) تصمیم گیری چند شاخصه (MADM) - Multi Attribute Decision Making))
2) تصمیم گیری چند هدفه (MODM) - Multi Objective Decision Making))

کلیه مباحث این درس در خصوص تصمیم‌گیری چند شاخصه بوده که در ابتدا به مباحث مقدماتی و آماده سازی داده ها و سپس انواع تکنیک های تصمیم گیری چندشاخصه خواهیم پرداخت  سپس در بخش  انتهایی به آموزش برخی از مهمترین انواع تکنیک های تصمیم گیری گروهی خواهیم پرداخت. به صورت کلی محوراصلی بر  اساس  تماما براساس تکنیک های تصمیم گیری چند شاخصه خواهد بود .

There are some methods for solving Multiple Criteria Decision-Making problems, of which one is the TOPSIS method. When data is nondeterministic like interval data, the method must be modified to show the correct result. In this research we present a new TOPSIS method for ranking DMUs with interval data yielding the interval score for each alternative, and in the end we show that when data is deterministic, our new method is the same as the conventional one.

The evolution from a focus on product design to one on process and product design in improving organizational competitiveness has included the development of a field of study called business process reengineering (BPR). BPR is a organizational development tool that requires a number of stages of analysis, design and implementation. The literature in the past few years has provided a number of tools and techniques to aid in BPR efforts. One area in this relatively new organizational change philosophy that has not received much attention is the selection or prioritization of a set of candidate business processes or projects that should undergo reengineering. Since business processes by definition are elements of a broader strategic system, the candidate evaluation and selection process must be strategically oriented. To aid in this evaluation process a strategic multiattribute evaluation and justification framework and methodology is presented. The methodology includes an activity based analysis and linkage of traditional (financial) and strategic considerations. The evaluation methodology may also have implications for post-implementation evaluation of BPR projects and other phases of BPR.

A cross-country pipeline construction project is exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors. These uncertainties can lead to several changes in project scope during the process of project execution. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved. A methodology is proposed for project control through risk analysis, contingency allocation and hierarchical planning models. Risk analysis is carried out through the analytic hierarchy process (AHP) due to the subjective nature of risks in construction projects. The results of risk analysis are used to determine the logical contingency for project control with the application of probability theory. Ultimate project control is carried out by hierarchical planning model which enables decision makers to take vital decisions during the changing environment of the construction period. Goal programming (GP), a multiple criteria decision-making technique, is proposed for model formulation because of its flexibility and priority-base structure. The project is planned hierarchically in three levels—project, work package and activity. GP is applied separately at each level. Decision variables of each model are different planning parameters of the project. In this study, models are formulated from the owner's perspective and its effectiveness in project control is demonstrated.

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was proposed by Hwang and Yoon as a multiple criteria decision making (MCDM) method, which identifies solutions from a finite set of alternatives. TOPSIS is based on the concept that the chosen alternative should have the shortest distance from the positive ideal solution (PIS) and the farthest distance from the negative ideal solution (NIS). In this study, the method was applied to evaluate the tourism destination competitiveness (TDC) of the Yangtze River Delta in China. This empirical study was based on a two-step procedure. The first procedure consisted of three hierarchies, four aspects and 35 evaluation indices, which were weighted by the information entropy weight (IEW). Secondly, the TOPSIS method was applied to the ranking analysis. This gave the most important index for each aspect by IEW. It also provided the ranking for 16 cities in the Yangtze River Delta based on four aspects, as well as the final overall ranking among them. Finally, the tactics and means for the cities to improve their tourism competitiveness were discussed. The results showed that TOPSIS & IEW can be implemented as an effective method in TDC evaluation.

In the global economy, the modern commercial and industrial organization needs to develop better methods of assessing the performance of the human resource than simply using performance measures such as ef®ciency or effectiveness. As organizations seek more aggressive ways to cut costs and to increase global competitiveness, the importance of establishing and sustaining high levels of employee performance increases. The main purpose of this paper is to solve the human performance improvement problem by employing Analytic Hierarchy Process (AHP) method. Decision makers (DMs) often deal with problems that involve multiple criteria. At given moments in time, companies will display characteristics that make certain factors; key factors in their competences. In this paper, we present a model, which illustrates the relations and importance between human performance improvement and the style of management. In using the AHP to model this problem, we developed a hierarchic structure to represent the problem of human performance management and made pairwise comparisons. In this paper, the AHP is suggested as a tool for implementing a multiple criteria performance improvement scheme. The AHP was used for the purpose of structuring and clarifying the relations and importance between human performance improvement and the style of management. The study found that in terms of company culture, participation, human capability, and attitudes the best management style in improving human performance is management by values.

This article presents a literature review of the applications of Analytic Hierarchy Process (AHP). AHP is a multiple criteria decision-making tool that has been used in almost all the applications related with decision-making. Out of many different applications of AHP, this article covers a select few, which could be of wide interest to the researchers and practitioners. The article critically analyses some of the papers published in international journals of high repute, and gives a brief idea about many of the referred publications. Papers are categorized according to the identified themes, and on the basis of the areas of applications. The references have also been grouped region-wise and year-wise in order to track the growth of AHP applications. To help readers extract quick and meaningful information, the references are summarized in various tabular formats and charts.

This paper provides a survey of the literature on multiple criteria decision-making (MCDM) applications to forestry problems undertaken in the last 30 years or so. More than 250 references regarding 9 forestry topics and 9 different MCDM approaches have been categorized and evaluated. This provides a unified source of references that could be useful for forest management students, researchers and practitioners. The paper ends with an assessment of the literature presented, aiming to reach some conclusions, as well as indicate future trends in this line of research. #

Production rate from oil fields is reduced due to various parameters with time. So it is needed to use some methods to compensate the reduction of production rate. Artificial lift method is the most suitable way to increase production rate. Artificial lift is one of the methods that increase the production rate by means of down hole pressure reduction. Artificial lift includes five methods and it is very important to select the best method, considering field conditions. In this paper, the best artificial lift is selected, using multiple criteria decision making models, such as; Technique for order preference by similarity to ideal solution (TOPSIS) and Elimination Et Choix Traduisant He realite( ELECTRE). In this research, 25 effective parameters are used for the method selection in one of the Iranian oil field. Comparing the obtained results from multiple criteria decision making methods, the best artificial lift method in the corresponding field is selected.

Our "information-oriented" society shows an increasing exigency of life-long learning. In such framework, the e-learning approach is becoming an important tool to allow the flexibility and quality requested by such a kind of learning process. In the recent past, a great number of online platforms have been introduced on the market showing different characteristics and services. With a plethora of e-learning providers and solutions available in the market, there is a new kind of problem faced by organizations consisting in the selection of the most suitable e-learning suite. This paper proposes a model for describing, characterizing and selecting e-learning platform. The e-learning solution selection is a multiple criteria decision-making problem that needs to be addressed objectively taking into consideration the relative weights of the criteria for any organization. We formulate the quoted multi criteria problem as a decision hierarchy to be solved using the analytic hierarchy process (AHP). In this paper we will show the general evaluation strategy and some obtained results using our model to evaluate some existing commercial platforms

Multiple criteria decision-making (MCDM) research has developed rapidly and has become a main area of research for dealing with complex decision problems. The purpose of the paper is to explore the performance evaluation model. This paper develops an evaluation model based on the fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution, fuzzy TOPSIS, to help the industrial practitioners for the performance evaluation in a fuzzy environment where the vagueness and subjectivity are handled with linguistic values parameterized by triangular fuzzy numbers. The proposed method enables decision analysts to better understand the complete evaluation process and provide a more accurate, effective, and systematic decision support tool.

The complex nature of construction projects and the involvement of a large number of unpredictable correlated factors make them susceptible to disputes. Although a wide range of dispute resolution mechanisms exists, experts in the construction industry favor arbitration over litigation when legally binding dispute resolution mechanisms are concerned. Because initiating a litigation or arbitration case against a business partner often severs the business relationship between them, predicting the arbitrator’s decision becomes valuable to the arbitrating parties. Because arbitration has been extensively treated as a game, and because the proposed approach relies on the wealth maximization concept, which is in turn dependent on the sum of utility sources of a firm, modeling arbitration is best achieved as a game with disputing parties’ utility profiles that would have an agreement zone. A construction-specific utility framework for the disputing parties arbitrating before a single arbitrator is proposed based on the additive expected utility theory. The proposed additive utility framework preserves the industry practicality and, most importantly, considers direct short-term factors and indirect long-term factors that would address factual disputes related to claim entitlement and quantification. It is expected that such a framework could then be used to identify utility equilibrium points between the disputing parties, which would serve the purpose of predicting the arbitration outcome.

Previous studies have documented that Data Envelopment Analysis (DEA) could be a good tool to evaluate fund performance, especially the performance of hedge funds as it can incorporate multiple risk-return attributes characterizing hedge fund's non normal return distribution in an unique performance score. The main purpose of this paper is to generalize this framework and to extend the use of DEA to the context of hedge fund selection when investors must face multi-dimensional constraints, each one associated to a relative importance level. Unlike previous studies which used DEA in an empirical framework, this research puts emphasis on methodological issues. I showed that DEA can be a good tailor-made decision-making tool to assist investors in selecting funds that correspond the most to their financial, risk-aversion, diversification and investment horizon constraints.

Selection of the suitable material handling equipment (MHE) is a very difficult task for the manufacturing companies because of the considerable capital investment required. There are many tangible and intangible factors for choosing the suitable MHE. Multiple criteria decision making (MCDM) has been found to be a useful approach to analyze these conflicting factors. The evaluation of MHE alternatives within the frame of various subjective criteria and the weights of the criteria are usually expressed in linguistic terms. This makes fuzzy logic a more natural approach to this kind of problems. This paper proposes a combined MCDM methodology for evaluation and selection of MHE types for a company in the steel construction industry in Istanbul, Turkey. Fuzzy analytic network process (FANP) is utilized for assigning weights of the criteria for MHE selection and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is used to determine the most proper system alternative using the criteria weights attained by FANP. The selection is based on the compatibility between MHE and production characteristics. Objective is to select the most efficient MHE considering also the cost efficiency. The study was followed by the sensitivity analyses of the results.

Multiple Criteria Decision Making (MCDM) shows signs of becoming a maturing field. There are four quite distinct families of methods: (i) the outranking, (ii) the value and utility theory based, (iii) the multiple objective programming, and (iv) group decision and negotiation theory based methods. Fuzzy MCDM has basically been developed along the same lines, although with the help of fuzzy set theory a number of innovations have been made possible; the most important methods are reviewed and a novel approach -interdependence in MCDM -is introduced.

Many spatial decision-making problems, such as site selection or land use allocation require the decision-maker to consider the impacts of choice-alternatives along multiple dimensions in order to choose the best alternative. The decisionmaking process, involving policy priorities, trade-offs, and uncertainties, can be aided by Multiple Criteria Decision-Making (MCDM) methods. This paper presents a framework for integrating geographical information systems (GIS) and MCDM methods. In this framework the MCDM methods are classified and matched with choice heuristics used by the decision-makers in the presence of competing alternatives and multiple evaluation criteria. Two strategies for integrating GIS with MCDM are proposed. The first strategy suggests linking GIS and MCDM techniques using a file exchange mechanism. The second strategy suggests integrating GIS and MCDM functions using a common database. The paper presents the implementation of the first strategy using PC-ARC/INFO, a file exchange module, and four different MCDM computer programs.

This paper describes the use of multiple criteria decision making techniques as decision tools for assessing criteria and indicators designed to evaluate sustainable forest management. Three techniques called ranking, rating, and pairwise comparisons are described and used within the framework of a generic set of criteria and indicators applied in a case study involving a forest concession in Kalimantan, Indonesia. For the case study, an assessment team consisting of national and international experts representing various disciplines was chosen to conduct an assessment of the forest concession. The criteria and indicators (C&I) developed by the Center for International Forestry Research was used as a reference. From this generic set of C&I, the assessment team made revisions to make the set more relevant to the prevailing conditions in the forest concession. This modi®ed set was used in the assessment of the concession.

This paper presents an original application of multiple criteria decision making analysis theory to the evaluation of aircraft selection problem. The selection of an optimal, efficient and reliable fleet, network and operations planning policy is one of the most important factors in aircraft selection problem. Given that decision making in aircraft selection involves the consideration of a number of opposite criteria and possible solutions, such a selection can be considered as a multiple criteria decision making analysis problem. This study presents a new integrated approach to decision making by considering the multiple criteria utility theory and the maximal regret minimization theory methods as well as aircraft technical, economical, and environmental aspects. Multiple criteria decision making analysis method uses different normalization techniques to allow criteria to be aggregated with qualitative and quantitative data of the decision problem. Therefore, selecting a suitable normalization technique for the model is also a challenge to provide data aggregation for the aircraft selection problem. To compare the impact of different normalization techniques on the decision problem, the vector, linear (sum), linear (max), and linear (max-min) data normalization techniques were identified to evaluate aircraft selection problem. As a logical implication of the proposed approach, it enhances the decision making process through enabling the decision maker to: (i) use higher level knowledge regarding the selection of criteria weights and the proposed technique, (ii) estimate the ranking of an alternative, under different data normalization techniques and integrated criteria weights after a posteriori analysis of the final rankings of alternatives. A set of commercial passenger aircraft were considered in order to illustrate the proposed approach. The obtained results of the proposed approach were compared using Spearman's rho tests. An analysis of the final rank stability with respect to the changes in criteria weights was also performed so as to assess the sensitivity of the alternative rankings obtained by the application of different data normalization techniques and the proposed approach.

During the past two and a half decades, there has been a steady growth in the number of methods for assisting decision making with multiple objectives. These methods, generally known as multiple criteria decision making (MCDM) methods, have found their applications in a number of areas. Specifically, this paper provides a survey of the reported applications of MCDM methods in higher education administration. Articles appearing since 1972 are analysed and classified according to the primary purpose of the application. It is observed that resource allocation has been the most significant reason for MCDM applications in higher education administration, followed by planning, evaluation and other purposes. Further, this review shows that future research can he focused on the area of sehedulin~ (particularly timetabling) development. The other research possibility is the usage of MCDM models at the federal and state government administration levels.

The aim of this paper is to report the finding from study to outline the underlying skill set required in getting and sustaining employment in the organised grocery and vegetable retail industry. The focus was 'Employability' which is neither one time attainable nor marketable vocational and academic skills just to create opportunity to get employment. An exploratory study has been carried out to understand the requirement of skill set in organised grocery and vegetable retailing for entry level jobs. Personal interview and questionnaire were the instruments used. Scope of the study to understand and identify required skills for entry level job in the organised grocery and vegetable retailing. Skill Matrix and employability skill set are formulated based on the study for entry level jobs in organised grocery and vegetable retailing sector.This study presents a comprehensive framework for selecting stores level managerial jobs by using Analytic Hierarchy Process (AHP). AHP method, expresses to determine the attributes in a multiple criteria decision-making problem in selection of personnel. Further scope for future research is enormous; study in the area of different or entire profile of retail jobs and geographical employability which is an influencing and deciding factor in organised grocery and vegetable employment.

Decision making is the process of finding the best option among the feasible alternatives. In classical multiple attribute decision making (MADM) methods, the ratings and the weights of the criteria are known precisely. Due to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. We design a model of TOPSIS for the fuzzy environment with the introduction of appropriate negations for obtaining ideal solutions. Here, we apply a new measurement of fuzzy distance value with a lower bound of alternatives. Then similarity degree is used for ranking of alternatives. Examples are shown to demonstrate capabilities of the proposed model.

Goal Programming (GP) is the most widely used approach in the field of multiple criteria decision making that enables the decision maker to incorporate numerous variations of constraints and goals, particularly in the field of Portfolio Selection (PS). This paper gives a brief review of the application of GP and its variants to Portfolio Selection and analysis problems. The paper firstly discusses the Multi-Criteria Decision Analysis in PS context in which GP is introduced as an important approach to PS Problems. An overview of performance measurement in portfolio selection context is also provided. Amongst the concluding remarks many issues in PS that may be addressed by GP such as multi-period, different measures of risk, and extended factors influencing portfolio selection are listed.

This paper considers the Bicriteria Shortest Path Problem (BSP) with the two conflicting objectives, minimizing the transportation cost and the total travel time. Bicriteria Shortest Path Problems, are often NP-hard problems [1], since obtaining the set of efficient solutions to a BSP problem is more difficult than solving the corresponding single-objective problem. This paper proposes a Bicriteria Genetic Algorithm approach to solve bicriteria shortest path problem.

This chapter provides a state-of-the-art account of the use of Sugeno integrals in decision evaluation, when it is difficult to use meaningful figures of merit when assessing the worth of a decision and when only a finite scale of, e.g., linguistic categories, can be used. Here, Sugeno integrals are thought of as idempotent lattice polynomial functions on a finite bounded chain, which makes it possible to assign importance weights to groups of criteria or states. Algebraic and behavioral characterizations of the Sugeno integral are presented and discussed, including in the special cases of weighted minima and maxima. Extensions of this framework are also surveyed, namely: the lexicographic refinements that increase the discrimination power of this approach; the use of local utility functions in order to cope with criteria having distinct rating scales; and the generalization of the criteria weighting scheme at work in Sugeno integrals. Another kind of extension considered is when ratings belong to a bipolar scale where good and bad figures are explicitly present, thus giving rise to the symmetric Sugeno integral or to the separate evaluation of pros and cons. Moreover, it is pointed out that Sugeno integrals encode decision rules and that this bridge leads to methods for extracting knowledge from qualitative data. The results of empirical studies of the latter are also presented and discussed, accordingly.

VIKOR is one of the multiple criteria decision making (MCDM) models to determine the preference ranking from a set of alternatives in the presence of conflicting criteria. The justification of VIKOR is to use the concept of the compromise programming to determine the preference ranking by the results of the individual and group regrets. However, VIKOR has a critical problem in deriving the preference ranking of alternative and this issue will be discussed later. In this paper, the perspective of regret theory is applied to explain the content of VIKOR and one revised model of VIKOR is proposed base on the concept of regret theory. Then, two examples are given to justify the proposed model and compare it with VIKOR and the regret model.

Nowadays, the requirement of flexibility in manufacturing has been increased rapidly because of severe market competition in which customer demand should be met in a right time and in a right way. Although there can be many reasons which affect productivity of the flexible manufacturing system (FMS), one of the crucial one is a scheduling policy which depends upon dispatching rules selection. Selection of a best dispatching rule can only be based on one or two criteria such as processing time, due date, or manufacturing system information in traditional methods such as mathematical programming, simulation, and heuristic algorithms. In addition, traditional methods have some weakness such as the following: first one is that dispatching rules do not allow the use of multiple criteria for evaluating process, second one is related with not considering most of the manufacturing system information, and the last one deals with selection decision not being a dynamic structure. In this study, an analytical network process model based on benefit, opportunity, cost, and risk has been developed in order to eradicate these weaknesses. The model is based on a multiple-criteria decision-making process which contains different performance criteria, details of FMS information, a company's strategic criteria, and different well-known dispatching rules. In addition, that fuzziness of information was also considered in the evaluation process.