This document proposes an innovative composite indicator to measure and control the performance o... more This document proposes an innovative composite indicator to measure and control the performance of production processes. The aim is to provide a tool for controlling the efficiency of the processes, assessed in relation to the number and the impact of occurring “errors”, which can take into account the opinion of experts in the specific domain. This allows for the definition of a more realistic and effective decision support system. Our composite indicator is based on an integrated approach based on Data Envelopment Analysis (DEA), and a new multi-criteria method such as Parsimonious Analytical Hierarchy Process (PAHP). The results obtained on a real test case, based on the automotive production domain, show that the composite indicator built with PAHP-DEA allows us to have clear evidence of the efficiency level of each process and the overall impact of errors on all the processes under evaluation. From a methodological point of view, we have for the first time combined the new thri...
Proceedings of the 8th International Conference on Operations Research and Enterprise Systems, 2019
Index tracking (IT) is an investment strategy aimed at replicating the performance of a given fin... more Index tracking (IT) is an investment strategy aimed at replicating the performance of a given financial index, taken as benchmark, over a given time horizon. This paper deals with the IT problem by proposing a stochastic programming model where the tracking error is measured by the Conditional Value at Risk (CVaR) measure. The multistage formulation overcomes the myopic view of the static models considering a longer time horizon and provides a more flexible paradigm where the initial strategy can be revised to account for changed market conditions. The proposed formulation presents a bi-objective function, where the two conflicting criteria wealth maximization and risk minimization, are jointly accounted for by properly choosing the weight to attribute to the two terms. The model is encapsulated within a rolling horizon scheme and solved iteratively exploiting each time the more update information in the generation of the scenario tree. The preliminary computational experiments carried out by considering as benchmark the Italian index FSTE-MIB seem to be promising and show that, on an out-of-sample analysis, the tracking portfolios follow the benchmark very closely, overcoming it on the long run.
This paper deals with the problem faced by an aggregator in defining the optimal tariff structure... more This paper deals with the problem faced by an aggregator in defining the optimal tariff structure for a group of prosumers aggregated within a coalition. The random nature of the main parameters involved in the decision process is explicitly accounted for by adopting the stochastic programming framework and, in particular, the paradigm of integrated chance constraints. Numerical experiments carried out on a realistic test case shows the efficacy of the proposed approach in providing more profitable rates for both consumers and producers with respect to the standard market alternatives.
This paper focuses on the home energy management for a residential prosumager with flexible loads... more This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochast...
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
the rapid growth in the use of recommendation systems in the tourism sector is mainly related to ... more the rapid growth in the use of recommendation systems in the tourism sector is mainly related to the possibility to access updated data deriving from social networks, thus providing more appropriate and personalized suggestions. the paper presents a tourist trip recommendation system that suggests personalized itineraries defined as sequence of point of interest (poi) to visit. the system core integrates two software modules: a neural network and an optimization engine. for every pair user-poi typology, the neural network provides, on the basis of the analysis of the social media data, a score between 0 and 1. these latter values are then used as input parameters for a routing optimization problem that suggests the itinerary by considering additional restriction, as, for example, time windows, budget and time limitations, specified by the end user. Being a computational demanding problem, the model solution is carried out by applying a heuristic approach that is proven to provide hi...
It is widely recognized that the adoption of collaborative organization models in the agri-food s... more It is widely recognized that the adoption of collaborative organization models in the agri-food sector can help farmers in rural areas to reach sustainable development goals. In any case, a holistic and coherent view of sustainability, organizational models and supporting technologies in the agri-food sector is still not present in the scientific literature. With this paper, we aim to fill this gap and to propose a framework that is useful to help scholars and practitioners in analyzing and designing sustainable Collaborative Networks in the agri-food sector
This paper focuses on the home energy management problem faced by a smart prosumer equipped with ... more This paper focuses on the home energy management problem faced by a smart prosumer equipped with photovoltaic panels and a storage system. Some of the home appliances (the shiftable ones) can be controlled in that the consumer may specify an operating time window within the load should be turned on. The inherent uncertainty affecting the main model parameters (i.e. loads and production from renewable) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The solution provides the prosumer with the optimal scheduling of the shiftable loads and the using profile of the storage system that guarantee the minimum expected energy procurement cost, taking into account the prosumer’s comfort. Preliminary results, collected on three different categories of residential prosumers, have shown the effectiveness of the proposed approach in terms of cost saving and the advantage related to the use of a stochastic programming approach over a deterministic formulation.
The Orienteering Problem (OP) is a routing problem which has many applications in logistics, tour... more The Orienteering Problem (OP) is a routing problem which has many applications in logistics, tourism and defense. Given a set of nodes, where each node represents a Point of Interest (POI), the orienteering problem aims to design a tour leaving from a starting POI, visiting a subset of POIs and finally arriving at the ending POI. The objective of the problem is to maximize the total score of the visited POIs while the total travel time and the total cost of the route do not exceed two predefined thresholds. Each POI is characterized by a score, a position, a visit time, and a time window in which the POI can be visited. This problem is often investigated to develop tourism trip planning mobile applications. Usually these apps must be able to generate good solutions in few seconds. Therefore, the use of efficient heuristic approaches to find good quality solutions is needed. In this paper we present a genetic algorithm framework combined with some local search operators to deal with the analyzed problem.
Scholars from different perspectives agree that agritourism can be the right tool to balance the ... more Scholars from different perspectives agree that agritourism can be the right tool to balance the needs of tourists with those of rural communities, offering real opportunities for economic and social development, while mitigating undesirable impacts on the environment. This paper aims to provide a holistic outlook of the different perspectives under which scientific literature deals with the topic of agritourism as a means to support the sustainable development of rural areas. To reach this aim, we performed a systematic review of the scientific literature in order to point out the linkages between agritourism and sustainability. We analyzed papers through a text mining solution based on the Latent Dirichlet Allocation (LDA) technique to point out the main topics around which the scientific literature on agritourism and sustainability has grown. Topics are further categorized in themes by means of an agglomerative hierarchical clustering procedure. Results are further analyzed to hi...
In this work we describe a new Smart Tourism System called SMARTCAL, born during the development ... more In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.
This paper deals with the optimal home energy management problem faced by a smart prosumer equipp... more This paper deals with the optimal home energy management problem faced by a smart prosumer equipped with PV panels and storage systems. The stochastic programming framework is adopted with the aim of explicitly accounting for the inherent uncertainty affecting the main problem parameters (i.e. generation from renewable energy sources and demands). The problem provides the prosumer with the optimal scheduling of the shiftable loads and operations of the available storage systems that minimizes the expected overall electricity cost. Preliminary results, collected on three different categories of residential prosumers, have shown the effectiveness of the proposed approach in terms of cost saving.
In this paper, we propose a dynamic and stochastic approach for an inventory routing problem in w... more In this paper, we propose a dynamic and stochastic approach for an inventory routing problem in which products with a high perishability must be delivered from a supplier to a set of customers. This problem falls within the agri-food supply chain (ASC) management field, which includes all the activities from production to distribution. The need for high-quality products that are subject to perishability is a critical issue to consider in the ASC optimization. Moreover, the demand uncertainty makes the problem very challenging. In order to effectively manage all these features, a rolling horizon approach based on a multistage stochastic linear program is proposed. Computational experiments over medium-size instances designed on the basis of the real data provided by an agri-food company operating in Southern Italy show the effectiveness of the proposed approach. Keywords Supply chain management • Agri-food inventory routing • Stochastic programming • Rolling horizon • Risk measure Communicated by M. Squillante.
In this paper we address a real industrial application involving a company that manages an e-mark... more In this paper we address a real industrial application involving a company that manages an e-marketplace for logistics services in the Italian territory. For the carriers, the main service offered by the company consists in the design of the optimal routes integrating additional delivery requests with those already in charge. The aim is to increase the profit exploiting the residual capacity of the vehicles. We model the problem as a multivehicle pickup and delivery problem with mandatory customers. We test the proposed approach on some real instances provided by the company. The computational results confirm the efficacy of the approach in providing more profitable solutions.
This paper deals with the problem of modelling complex transaction cost structures within portfol... more This paper deals with the problem of modelling complex transaction cost structures within portfolio management models in an efficient and effective way. We consider a general structure of transaction costs, where the applied commissions depend on the range of traded monetary amount and we use this general structure within a portfolio optimization problem with rebalancing decisions in response to new market conditions. The presence of transaction costs reduces the fund's capital and should be properly accounted for to avoid substantial costs that impact on portfolio performance. In this paper we present a mixed integer model equipped with a specialized Branch and Bound method that exploits the specific formulation of the trading operations. Computational experiments, carried out on transaction cost structures offered by real-life traders, have shown the effectiveness of the proposed model and the computational efficiency of the solution approach.
District heating networks are commonly addressed in the literature as one of the most effective s... more District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand-outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
The definition of the electric energy procurement plan represents a fundamental problem that any ... more The definition of the electric energy procurement plan represents a fundamental problem that any consumer has to deal with. Bilateral contracts, electricity market and self-production are the main supply sources that should be properly combined to satisfy the energy demand over a given time horizon at the minimum cost. The problem is made more complex by the presence of uncertainty, mainly related to the energy requirements and electricity market prices. Ignoring the uncertain nature of these elements can lead to the definition of procurement plans which are infeasible or overly expensive in a real setting. In this paper, we deal with the procurement problem under uncertainty by adopting the paradigm of joint chance constraints to define reliable plans that are feasible with a high probability level. Moreover, the proposed model includes in the objective function a risk measure to control undesirable effects caused by the random variations of the electricity market prices. The proposed model is applied to a real test case. The results show the benefit deriving from the stochastic optimization approach and the effect of considering different levels of risk aversion.
In this paper we deal with the definition of a decisional model for a producer operating in a mul... more In this paper we deal with the definition of a decisional model for a producer operating in a multi-auction electricity market. The decisions to be taken concern the commitment of the generation plants and the quantity of energy required to offer to each auction and to cover the bilateral contracts. We propose a Multistage Stochastic Programming model in which the randomness of the clearing prices is represented by means of a scenario tree. The risk is modelled using a Conditional Value at Risk term in the objective function. Experimental results are reported to show the validity of our model and to discuss the influence of the risk parameters on the optimal value.
International Series in Operations Research & Management Science, 2011
The European market for corporate bonds has grown significantly over the last two decades to beco... more The European market for corporate bonds has grown significantly over the last two decades to become a preferable financing channel for large corporations in the local and Eurobond markets. The 2008 credit crisis has, however, dramatically changed corporations funding opportunities with similar effects on borrowing policies of sovereigns as well. Accordingly institutional and individual investors have progressively reduced the share of credit risky instruments in their portfolios. This chapter investigates the potential of multistage stochastic programming to provide the desired market and credit risk control for such portfolios over the recent, unprecedented financial turmoil. We consider a Eurobond portfolio, traded in the secondary market, subject to interest and credit risk and analyse whether a jumpto-default risk model and a dynamic control policy would have reduced the impact of severe market shocks on the portfolios during the crisis, to limit the systemic impact of investment strategies. The methodology is shown to provide an effective alternative to popular hedging techniques based on credit derivatives at a time in which such markets became extremely illiquid during the Fall of 2008.
This document proposes an innovative composite indicator to measure and control the performance o... more This document proposes an innovative composite indicator to measure and control the performance of production processes. The aim is to provide a tool for controlling the efficiency of the processes, assessed in relation to the number and the impact of occurring “errors”, which can take into account the opinion of experts in the specific domain. This allows for the definition of a more realistic and effective decision support system. Our composite indicator is based on an integrated approach based on Data Envelopment Analysis (DEA), and a new multi-criteria method such as Parsimonious Analytical Hierarchy Process (PAHP). The results obtained on a real test case, based on the automotive production domain, show that the composite indicator built with PAHP-DEA allows us to have clear evidence of the efficiency level of each process and the overall impact of errors on all the processes under evaluation. From a methodological point of view, we have for the first time combined the new thri...
Proceedings of the 8th International Conference on Operations Research and Enterprise Systems, 2019
Index tracking (IT) is an investment strategy aimed at replicating the performance of a given fin... more Index tracking (IT) is an investment strategy aimed at replicating the performance of a given financial index, taken as benchmark, over a given time horizon. This paper deals with the IT problem by proposing a stochastic programming model where the tracking error is measured by the Conditional Value at Risk (CVaR) measure. The multistage formulation overcomes the myopic view of the static models considering a longer time horizon and provides a more flexible paradigm where the initial strategy can be revised to account for changed market conditions. The proposed formulation presents a bi-objective function, where the two conflicting criteria wealth maximization and risk minimization, are jointly accounted for by properly choosing the weight to attribute to the two terms. The model is encapsulated within a rolling horizon scheme and solved iteratively exploiting each time the more update information in the generation of the scenario tree. The preliminary computational experiments carried out by considering as benchmark the Italian index FSTE-MIB seem to be promising and show that, on an out-of-sample analysis, the tracking portfolios follow the benchmark very closely, overcoming it on the long run.
This paper deals with the problem faced by an aggregator in defining the optimal tariff structure... more This paper deals with the problem faced by an aggregator in defining the optimal tariff structure for a group of prosumers aggregated within a coalition. The random nature of the main parameters involved in the decision process is explicitly accounted for by adopting the stochastic programming framework and, in particular, the paradigm of integrated chance constraints. Numerical experiments carried out on a realistic test case shows the efficacy of the proposed approach in providing more profitable rates for both consumers and producers with respect to the standard market alternatives.
This paper focuses on the home energy management for a residential prosumager with flexible loads... more This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochast...
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
the rapid growth in the use of recommendation systems in the tourism sector is mainly related to ... more the rapid growth in the use of recommendation systems in the tourism sector is mainly related to the possibility to access updated data deriving from social networks, thus providing more appropriate and personalized suggestions. the paper presents a tourist trip recommendation system that suggests personalized itineraries defined as sequence of point of interest (poi) to visit. the system core integrates two software modules: a neural network and an optimization engine. for every pair user-poi typology, the neural network provides, on the basis of the analysis of the social media data, a score between 0 and 1. these latter values are then used as input parameters for a routing optimization problem that suggests the itinerary by considering additional restriction, as, for example, time windows, budget and time limitations, specified by the end user. Being a computational demanding problem, the model solution is carried out by applying a heuristic approach that is proven to provide hi...
It is widely recognized that the adoption of collaborative organization models in the agri-food s... more It is widely recognized that the adoption of collaborative organization models in the agri-food sector can help farmers in rural areas to reach sustainable development goals. In any case, a holistic and coherent view of sustainability, organizational models and supporting technologies in the agri-food sector is still not present in the scientific literature. With this paper, we aim to fill this gap and to propose a framework that is useful to help scholars and practitioners in analyzing and designing sustainable Collaborative Networks in the agri-food sector
This paper focuses on the home energy management problem faced by a smart prosumer equipped with ... more This paper focuses on the home energy management problem faced by a smart prosumer equipped with photovoltaic panels and a storage system. Some of the home appliances (the shiftable ones) can be controlled in that the consumer may specify an operating time window within the load should be turned on. The inherent uncertainty affecting the main model parameters (i.e. loads and production from renewable) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The solution provides the prosumer with the optimal scheduling of the shiftable loads and the using profile of the storage system that guarantee the minimum expected energy procurement cost, taking into account the prosumer’s comfort. Preliminary results, collected on three different categories of residential prosumers, have shown the effectiveness of the proposed approach in terms of cost saving and the advantage related to the use of a stochastic programming approach over a deterministic formulation.
The Orienteering Problem (OP) is a routing problem which has many applications in logistics, tour... more The Orienteering Problem (OP) is a routing problem which has many applications in logistics, tourism and defense. Given a set of nodes, where each node represents a Point of Interest (POI), the orienteering problem aims to design a tour leaving from a starting POI, visiting a subset of POIs and finally arriving at the ending POI. The objective of the problem is to maximize the total score of the visited POIs while the total travel time and the total cost of the route do not exceed two predefined thresholds. Each POI is characterized by a score, a position, a visit time, and a time window in which the POI can be visited. This problem is often investigated to develop tourism trip planning mobile applications. Usually these apps must be able to generate good solutions in few seconds. Therefore, the use of efficient heuristic approaches to find good quality solutions is needed. In this paper we present a genetic algorithm framework combined with some local search operators to deal with the analyzed problem.
Scholars from different perspectives agree that agritourism can be the right tool to balance the ... more Scholars from different perspectives agree that agritourism can be the right tool to balance the needs of tourists with those of rural communities, offering real opportunities for economic and social development, while mitigating undesirable impacts on the environment. This paper aims to provide a holistic outlook of the different perspectives under which scientific literature deals with the topic of agritourism as a means to support the sustainable development of rural areas. To reach this aim, we performed a systematic review of the scientific literature in order to point out the linkages between agritourism and sustainability. We analyzed papers through a text mining solution based on the Latent Dirichlet Allocation (LDA) technique to point out the main topics around which the scientific literature on agritourism and sustainability has grown. Topics are further categorized in themes by means of an agglomerative hierarchical clustering procedure. Results are further analyzed to hi...
In this work we describe a new Smart Tourism System called SMARTCAL, born during the development ... more In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.
This paper deals with the optimal home energy management problem faced by a smart prosumer equipp... more This paper deals with the optimal home energy management problem faced by a smart prosumer equipped with PV panels and storage systems. The stochastic programming framework is adopted with the aim of explicitly accounting for the inherent uncertainty affecting the main problem parameters (i.e. generation from renewable energy sources and demands). The problem provides the prosumer with the optimal scheduling of the shiftable loads and operations of the available storage systems that minimizes the expected overall electricity cost. Preliminary results, collected on three different categories of residential prosumers, have shown the effectiveness of the proposed approach in terms of cost saving.
In this paper, we propose a dynamic and stochastic approach for an inventory routing problem in w... more In this paper, we propose a dynamic and stochastic approach for an inventory routing problem in which products with a high perishability must be delivered from a supplier to a set of customers. This problem falls within the agri-food supply chain (ASC) management field, which includes all the activities from production to distribution. The need for high-quality products that are subject to perishability is a critical issue to consider in the ASC optimization. Moreover, the demand uncertainty makes the problem very challenging. In order to effectively manage all these features, a rolling horizon approach based on a multistage stochastic linear program is proposed. Computational experiments over medium-size instances designed on the basis of the real data provided by an agri-food company operating in Southern Italy show the effectiveness of the proposed approach. Keywords Supply chain management • Agri-food inventory routing • Stochastic programming • Rolling horizon • Risk measure Communicated by M. Squillante.
In this paper we address a real industrial application involving a company that manages an e-mark... more In this paper we address a real industrial application involving a company that manages an e-marketplace for logistics services in the Italian territory. For the carriers, the main service offered by the company consists in the design of the optimal routes integrating additional delivery requests with those already in charge. The aim is to increase the profit exploiting the residual capacity of the vehicles. We model the problem as a multivehicle pickup and delivery problem with mandatory customers. We test the proposed approach on some real instances provided by the company. The computational results confirm the efficacy of the approach in providing more profitable solutions.
This paper deals with the problem of modelling complex transaction cost structures within portfol... more This paper deals with the problem of modelling complex transaction cost structures within portfolio management models in an efficient and effective way. We consider a general structure of transaction costs, where the applied commissions depend on the range of traded monetary amount and we use this general structure within a portfolio optimization problem with rebalancing decisions in response to new market conditions. The presence of transaction costs reduces the fund's capital and should be properly accounted for to avoid substantial costs that impact on portfolio performance. In this paper we present a mixed integer model equipped with a specialized Branch and Bound method that exploits the specific formulation of the trading operations. Computational experiments, carried out on transaction cost structures offered by real-life traders, have shown the effectiveness of the proposed model and the computational efficiency of the solution approach.
District heating networks are commonly addressed in the literature as one of the most effective s... more District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand-outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
The definition of the electric energy procurement plan represents a fundamental problem that any ... more The definition of the electric energy procurement plan represents a fundamental problem that any consumer has to deal with. Bilateral contracts, electricity market and self-production are the main supply sources that should be properly combined to satisfy the energy demand over a given time horizon at the minimum cost. The problem is made more complex by the presence of uncertainty, mainly related to the energy requirements and electricity market prices. Ignoring the uncertain nature of these elements can lead to the definition of procurement plans which are infeasible or overly expensive in a real setting. In this paper, we deal with the procurement problem under uncertainty by adopting the paradigm of joint chance constraints to define reliable plans that are feasible with a high probability level. Moreover, the proposed model includes in the objective function a risk measure to control undesirable effects caused by the random variations of the electricity market prices. The proposed model is applied to a real test case. The results show the benefit deriving from the stochastic optimization approach and the effect of considering different levels of risk aversion.
In this paper we deal with the definition of a decisional model for a producer operating in a mul... more In this paper we deal with the definition of a decisional model for a producer operating in a multi-auction electricity market. The decisions to be taken concern the commitment of the generation plants and the quantity of energy required to offer to each auction and to cover the bilateral contracts. We propose a Multistage Stochastic Programming model in which the randomness of the clearing prices is represented by means of a scenario tree. The risk is modelled using a Conditional Value at Risk term in the objective function. Experimental results are reported to show the validity of our model and to discuss the influence of the risk parameters on the optimal value.
International Series in Operations Research & Management Science, 2011
The European market for corporate bonds has grown significantly over the last two decades to beco... more The European market for corporate bonds has grown significantly over the last two decades to become a preferable financing channel for large corporations in the local and Eurobond markets. The 2008 credit crisis has, however, dramatically changed corporations funding opportunities with similar effects on borrowing policies of sovereigns as well. Accordingly institutional and individual investors have progressively reduced the share of credit risky instruments in their portfolios. This chapter investigates the potential of multistage stochastic programming to provide the desired market and credit risk control for such portfolios over the recent, unprecedented financial turmoil. We consider a Eurobond portfolio, traded in the secondary market, subject to interest and credit risk and analyse whether a jumpto-default risk model and a dynamic control policy would have reduced the impact of severe market shocks on the portfolios during the crisis, to limit the systemic impact of investment strategies. The methodology is shown to provide an effective alternative to popular hedging techniques based on credit derivatives at a time in which such markets became extremely illiquid during the Fall of 2008.
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