SAT-based Leximax Optimisation Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00364161" target="_blank" >RIV/68407700:21730/22:00364161 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.4230/LIPIcs.SAT.2022.29" target="_blank" >https://doi.org/10.4230/LIPIcs.SAT.2022.29</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4230/LIPIcs.SAT.2022.29" target="_blank" >10.4230/LIPIcs.SAT.2022.29</a>
Alternative languages
Result language
angličtina
Original language name
SAT-based Leximax Optimisation Algorithms
Original language description
In several real-world problems, it is often the case that the goal is to optimise several objective functions. However, usually there is not a single optimal objective vector. Instead, there are many optimal objective vectors known as Pareto-optima. Finding all Pareto-optima is computationally expensive and the number of Pareto-optima can be too large for a user to analyse. A compromise can be made by defining an optimisation criterion that integrates all objective functions. In this paper we propose several SAT-based algorithms to solve multi-objective optimisation problems using the leximax criterion. The leximax criterion is used to obtain a Pareto-optimal solution with a small trade-off between the objective functions, which is suitable in problems where there is an absence of priorities between the objective functions. Experimental results on the Multi-Objective Package Upgradeability Optimisation problem show that the SAT-based algorithms are able to outperform the Integer Linear Programming (ILP) approach when using non-commercial ILP solvers. Additionally, experimental results on selected instances from the MaxSAT evaluation adapted to the multi-objective domain show that our approach outperforms the ILP approach using commercial solvers.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)
ISBN
978-3-95977-242-6
ISSN
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e-ISSN
1868-8969
Number of pages
29
Pages from-to
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Publisher name
Dagstuhl Publishing,
Place of publication
Saarbrücken
Event location
Haifa
Event date
Aug 2, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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