Metaheuristic Solver for Problems with Permutative Representation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00361949" target="_blank" >RIV/68407700:21230/23:00361949 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/23:00361949

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-031-19958-5_5" target="_blank" >https://doi.org/10.1007/978-3-031-19958-5_5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-19958-5_5" target="_blank" >10.1007/978-3-031-19958-5_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Metaheuristic Solver for Problems with Permutative Representation

Popis výsledku v původním jazyce

Today, a large proportion of combinatorial optimization problems can be efficiently formulated as a mixed-integer program and solved with an exact solver. However, exact solvers do not scale well and thus custom metaheuristic algorithms are being designed to provide better scalability at the cost of no optimality guarantees and time-consuming development. This paper proposes a novel formalism for a large class of problems with permutative representation, together with a metaheuristic solver addressing these problems. This approach combines the advantages of both exact and metaheuristic solvers: straightforward problem formulation, scalability, low design time, and ability to find high quality solutions. Three different problems are formulated in the proposed formalism and solved with the proposed solver. The solver is benchmarked against the Gurobi Optimizer and significantly outperforms it in experiments with a fixed computational budget.

Název v anglickém jazyce

Metaheuristic Solver for Problems with Permutative Representation

Popis výsledku anglicky

Today, a large proportion of combinatorial optimization problems can be efficiently formulated as a mixed-integer program and solved with an exact solver. However, exact solvers do not scale well and thus custom metaheuristic algorithms are being designed to provide better scalability at the cost of no optimality guarantees and time-consuming development. This paper proposes a novel formalism for a large class of problems with permutative representation, together with a metaheuristic solver addressing these problems. This approach combines the advantages of both exact and metaheuristic solvers: straightforward problem formulation, scalability, low design time, and ability to find high quality solutions. Three different problems are formulated in the proposed formalism and solved with the proposed solver. The solver is benchmarked against the Gurobi Optimizer and significantly outperforms it in experiments with a fixed computational budget.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Intelligent Computing & Optimization

ISBN

978-3-031-19957-8

ISSN

2367-3370

e-ISSN

2367-3389

Počet stran výsledku

13

Strana od-do

42-54

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Hua Hin

Datum konání akce

27. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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