The purpose of this paper is to discuss the use of Value Efficiency Analysis (VEA) in efficiency evaluation when preference information is taken into account. Value efficiency analysis is an approach, which applies th...
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The purpose of this paper is to discuss the use of Value Efficiency Analysis (VEA) in efficiency evaluation when preference information is taken into account. Value efficiency analysis is an approach, which applies the ideas developed for multiple objective linear programming (MOLP) to Data Envelopment Analysis (DEA). Preference information is given through the desirable structure of input- and output-values. The same values can be used for all units under evaluation or the values can be specific for each unit. A decision-maker can specify the input- and output-values subjectively without any support or (s)he can use a multiple criteria support system to assist him/her to find those values on the efficient frontier. The underlying assumption is that the most preferred values maximize the decision-maker's implicitly known value function in a production possibility set or a subset. The purpose of value efficiency analysis is to estimate a need to increase outputs and/or decrease inputs for reaching the indifference contour of the value function at the optimum. In this paper, we briefly review the main ideas in value efficiency analysis and discuss practical aspects related to the use of value efficiency analysis. We also consider some extensions.
multiple objective linear programming problems frequently arise in various applications of computational and data science. An important class of iterative techniques for numerically solving these problems is based on ...
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ISBN:
(纸本)9783319951652;9783319951645
multiple objective linear programming problems frequently arise in various applications of computational and data science. An important class of iterative techniques for numerically solving these problems is based on Benson's algorithm. This algorithm starts with an initial outer approximation of a polyhedron and then iteratively refines these outer approximations until a solution is found. This algorithm is an archetype of a class of methods that have been extensively studied serially. Today, however, there is hardly any discussion in the open literature on the difficulties encountered when executing this algorithm in parallel. To fill this gap, we report on numerical experiences when parallelizing Benson's algorithm on two different shared-memory computers. More precisely, we quantify the performance of a parallelized version of this algorithm on two Intel systems (single socket Core i7-6700 with up to 4 threads and dual socket Xeon E5-2650v4 using up to 24 threads). We show that parallelizing Benson's algorithm has its performance limitations caused by memory bandwidth saturation. We also sketch opportunities for future research directions on techniques that could improve the performance of Benson-type algorithms on parallel computers.
Data envelopment analysis (DEA) is a nonparametric frontier assessment method used to evaluate the relative efficiency of similar decision-making units (DMUs). This method provides benchmarking information regarding t...
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Data envelopment analysis (DEA) is a nonparametric frontier assessment method used to evaluate the relative efficiency of similar decision-making units (DMUs). This method provides benchmarking information regarding the removal of inefficiency. In conventional DEA models, the view of the decision maker (DM) is ignored and the performance of each DMU is solely determined by the observations retrieved. The current paper exploits the structural similarity existing between DEA and multipleobjectiveprogramming to define a model that incorporates the preferences of DMs in the evaluation process of DMUs. Given the potential unfeasibility of the input and output targets selected by the DM, the model defines an interactive procedure that considers minimum and maximum acceptable objective levels. Given the feasible levels located closer to the targets selected by the DM, a program improving upon the feasible allocations is designed so that the suggested benchmark approximates the requirements fixed by the DM as much as possible. A real-life case study is included to illustrate the efficacy and applicability of the proposed hybrid procedure.
An economy-energy-environment multipleobjective model based on the linear structure of inter-industry production linkages is presented. Axes of evaluation consistent with sustainable energy strategies, economic growt...
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An economy-energy-environment multipleobjective model based on the linear structure of inter-industry production linkages is presented. Axes of evaluation consistent with sustainable energy strategies, economic growth, social welfare and environmental friendliness are explicitly considered. The aim of this study is to provide decision-makers with a comprehensive model which allows to assess environmental burdens (global warming potential and acidification potential) with respect to changes in economic activities consistent with distinct policy measures. (C) 2003 Elsevier B.V. All rights reserved.
In this paper the potentialities of TRIMAP to provide decision support in multiobjective problems with multiple decision makers are exploited. TRIMAP is an interactive three-objectivelinearprogramming package which ...
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This paper describes the decision support approach used in the development process of the S Group's Prisma hypermarket chain in Finland. The management was looking for a new and sustainable operating model for the...
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This paper describes the decision support approach used in the development process of the S Group's Prisma hypermarket chain in Finland. The management was looking for a new and sustainable operating model for the rapidly growing chain, and contacted the author to consult in the process. Fierce competition forced the search for new business ideas, tools and methods that would provide a clear competitive advantage. To find new perspectives, we decided to use statistical approaches and various decision support system options, such as multi-criteria modelling. A database was available for research and analysis, including data on purchasing behavior and key performance indicators (KPI). The approach had to take into account the role and impact of customers. It was highly important to include customer behavior in the analysis using shopping basket data. Shopping basket data was central in the current paper. From these, an observation matrix was created combining shopping basket data, product data and customer background information. Using multivariate methods, customer groupings and profiles were created with the data from the observation matrix. Using the customer profile and KPI data, a multi-criteria decision support system was produced to support strategic planning. The decision support system (DSS) model was created together with a market chain operational expert and an external methodological expert. We used the VIG software package developed by Korhonen (Belg J Oper Res Stat Comput Sci 27(3):15, 1987) to solve the problem because it is easy to use and requires no prior knowledge of computers or multi-objectivelinearprogramming models. Pareto Race plays a central role in the VIG system. The chain expert easily learned how to use and work with the model. The results were immediately visible and could be used to examine alternatives and assess their appropriateness. It was decided to present five different scenarios to the hypermarket chain management. The main obj
The problem (P) of optimizing a linear function over the efficient set of a multipleobjectivelinear program has many important applications in multiple criteria decision making. Since the efficient set is in general...
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In many applications, finding target unit is required, particularly when decision maker (DM) wants to search along the efficient frontier to locate the most preferred solution. Wong et al. [Wong, Y.H., Luque, M., Yang...
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In recent years, the relation between data envelopment analysis and multiple objective linear programming has received a great deal of attention from researchers. However, there are two difficulties in doing an object...
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In recent years, the relation between data envelopment analysis and multiple objective linear programming has received a great deal of attention from researchers. However, there are two difficulties in doing an objective evaluation of the performance of decision making units. The first one is how to treat undesirable factors jointly produced with the desirable factors and the second one is how to treat with imprecise data. In this paper, we establish an equivalence relation between multiple objective linear programming and the output-oriented Banker, Charnes, Cooper(BCC) model in the present of undesirable factors and fuzzy data such that the decision maker's preference can be taken into account in an interactive fashion for finding target unit.
Radial projection is a standard technique applied in data envelopment analysis (DEA) to calculate efficiency scores for input and/or output variables. In this paper, we have studied the appropriateness of radial proje...
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Radial projection is a standard technique applied in data envelopment analysis (DEA) to calculate efficiency scores for input and/or output variables. In this paper, we have studied the appropriateness of radial projection for target setting. We have created a situation where the decision making units (DMUs) are free to choose their own target values on the efficient frontier and then compared the results to those of radial projection. In practice, target values are primarily used for future goal attainment;hence, not only preferences but also, and on the whole, change in time frame, affect the choice of target values. Based on that, we conducted an empirical experiment with an aim to study how the DMUs choose their most preferred target values on the efficient frontier. The subjects, who all were students of the Helsinki School of Economics, were given the freedom to explore their personalized efficient frontiers by using a multiple objective linear programming (MOLP) approach. To study various and relevant scenarios, the personalized efficient frontiers for all students were constructed in such a way that the current position of each student in relation to the frontier made him/her inefficient, efficient, or super-efficient. The results show that the use of radial projection for target setting is too restrictive.
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