A Decision Support System for Solving Multiple Criteria Optimization Problems

In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting dif...

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Main Authors: Ernestas FILATOVAS, Olga KURASOVA
Format: Article
Language:English
Published: Vilnius University 2011-10-01
Series:Informatics in Education
Subjects:
Online Access:https://infedu.vu.lt/doi/10.15388/infedu.2011.14
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author Ernestas FILATOVAS
Olga KURASOVA
author_facet Ernestas FILATOVAS
Olga KURASOVA
author_sort Ernestas FILATOVAS
collection DOAJ
description In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria and solving single-criterion optimization problems (SOPs). However, the WS approach does not guarantee either finding evenly distributed solutions of a Pareto front, or finding Pareto optimal solutions in non-convex regions. In order to solve the problems, some methods have been proposed. In this paper, an adaptive weighted-sum (AWS) approach has been used. We suggest presenting the solutions, obtained not only by the weighted-sum method, but also by the adaptive weighted-sum approach, to a decision maker (DM). Thus the decision making will be facilitated.
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spelling doaj.art-7df9f02e7d514586a742a1ae6e36c14d2022-12-22T04:03:33ZengVilnius UniversityInformatics in Education1648-58312335-89712011-10-0110221322410.15388/infedu.2011.14A Decision Support System for Solving Multiple Criteria Optimization ProblemsErnestas FILATOVAS0Olga KURASOVA1Vilnius University, Institute of Mathematics and Informatics Akademijos 4, LT-08663 Vilnius, LihuaniaVilnius University, Institute of Mathematics and Informatics Akademijos 4, LT-08663 Vilnius, LihuaniaIn this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria and solving single-criterion optimization problems (SOPs). However, the WS approach does not guarantee either finding evenly distributed solutions of a Pareto front, or finding Pareto optimal solutions in non-convex regions. In order to solve the problems, some methods have been proposed. In this paper, an adaptive weighted-sum (AWS) approach has been used. We suggest presenting the solutions, obtained not only by the weighted-sum method, but also by the adaptive weighted-sum approach, to a decision maker (DM). Thus the decision making will be facilitated.https://infedu.vu.lt/doi/10.15388/infedu.2011.14multiple criteria optimizationdecision support systeminteractive optimizationdecision makingPareto front
spellingShingle Ernestas FILATOVAS
Olga KURASOVA
A Decision Support System for Solving Multiple Criteria Optimization Problems
Informatics in Education
multiple criteria optimization
decision support system
interactive optimization
decision making
Pareto front
title A Decision Support System for Solving Multiple Criteria Optimization Problems
title_full A Decision Support System for Solving Multiple Criteria Optimization Problems
title_fullStr A Decision Support System for Solving Multiple Criteria Optimization Problems
title_full_unstemmed A Decision Support System for Solving Multiple Criteria Optimization Problems
title_short A Decision Support System for Solving Multiple Criteria Optimization Problems
title_sort decision support system for solving multiple criteria optimization problems
topic multiple criteria optimization
decision support system
interactive optimization
decision making
Pareto front
url https://infedu.vu.lt/doi/10.15388/infedu.2011.14
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