Finding all equitably non-dominated points of multiobjective integer programming problems

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buir.advisorKarsu, Özlem
dc.contributor.authorUlutaş, Seyit
dc.date.accessioned2023-09-19T06:46:29Z
dc.date.available2023-09-19T06:46:29Z
dc.date.copyright2023-09
dc.date.issued2023-09
dc.date.submitted2023-09-18
dc.departmentDepartment of Industrial Engineering
dc.descriptionCataloged from PDF version of article.
dc.descriptionThesis (Master's): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2023.
dc.descriptionIncludes bibliographical references (leaves 54-58).
dc.description.abstractEquitable multiobjective programming (E-MOP) problems are multiobjective programming problems of a special type. In E-MOP, the decision-maker has equity concerns and hence has an equitable rational preference model. In line with this, our aim is to find all equitably non-dominated points (EN) of the multi-objective integer problems. There are different approaches to solving E-MOP problems. We use equitable aggregation functions and develop two different algorithms; one for equitable biobjective integer programming (E-BOIP) problems and one for equitable multiobjective integer programming (E-MOIP) problems with more than two objectives. In the first algorithm, we solve Pascoletti Serafini (PS) scalarization models iteratively while ensuring getting a weakly equitably non-dominated point in each iteration. In the second algorithm, we use cumulative ordered weighted average in the ExA algorithm of Özpeynirci and Köksalan [1] to find all extreme supported equitably non-dominated points (ESN) first. After finding all ESNs, we use them to define the regions that could contain EN. Then we use split algorithm and find all the remaining ENs. We also provide a split only version of the algorithm since the process of finding all ESNs could be time consuming. We compare two versions in multiobjective assignment and knapsack problem instances. Although the split only version is quicker, the original version of the algorithm is useful since it gives information about the weight space decomposition of ESNs. The weight space decomposition discussion is also provided.
dc.description.degreeM.S.
dc.description.statementofresponsibilityby Seyit Ulutaş
dc.embargo.release2024-03-18
dc.format.extentix, 62 leaves : charts ; 30 cm.
dc.identifier.itemidB162518
dc.identifier.urihttps://hdl.handle.net/11693/113876
dc.language.isoEnglish
dc.publisherBilkent University
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEquitable optimization
dc.subjectMultiobjective integer programming
dc.subjectPasco-letti Serafini scalarization
dc.subjectSplit algorithm
dc.subjectWeight space decomposition
dc.titleFinding all equitably non-dominated points of multiobjective integer programming problems
dc.title.alternativeÇok amaçlı tam sayılı programlama problemlerinin tüm eşitlikçi baskın noktalarını bulma
dc.typeThesis

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