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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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

  • e-ISSN

    1868-8969

  • Number of pages

    29

  • Pages from-to

  • 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