Detail publikace

How to start a heuristic? Utilizing lower bounds for solving the quadratic assignment problem

MATOUŠEK, R. DOBROVSKÝ, L. KŮDELA, J.

Originální název

How to start a heuristic? Utilizing lower bounds for solving the quadratic assignment problem

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

The Quadratic Assignment Problem (QAP) is one of the classical combinatorial optimization problems and is known for its diverse applications. The QAP is an NP-hard optimization problem which attracts the use of heuristic or metaheuristic algorithms that can find quality solutions in an acceptable computation time. On the other hand, there is quite a broad spectrum of mathematical programming techniques that were developed for finding the lower bounds for the QAP. This paper presents a fusion of the two approaches whereby the solutions from the computations of the lower bounds are used as the starting points for a metaheuristic, called HC12, which is implemented on a GPU CUDA platform. We perform extensive computational experiments that demonstrate that the use of these lower bounding techniques for the construction of the starting points has a significant impact on the quality of the resulting solutions.

Klíčová slova

Heuristics; Lower bounds; Metaheuristics; Quadratic assignment problem; Starting values

Autoři

MATOUŠEK, R.; DOBROVSKÝ, L.; KŮDELA, J.

Vydáno

31. 12. 2021

Nakladatel

Growing Science

ISSN

1923-2934

Periodikum

International Journal of Industrial Engineering Computations

Ročník

13

Číslo

2

Stát

Kanada

Strany od

151

Strany do

164

Strany počet

14

URL

http://www.growingscience.com/ijiec/Vol13/IJIEC_2021_33.pdf

Plný text v Digitální knihovně

http://hdl.handle.net/11012/203280

BibTex

@article{BUT175648,
  author="Radomil {Matoušek} and Ladislav {Dobrovský} and Jakub {Kůdela}",
  title="How to start a heuristic? Utilizing lower bounds for solving the quadratic assignment problem",
  journal="International Journal of Industrial Engineering Computations",
  year="2021",
  volume="13",
  number="2",
  pages="151--164",
  doi="10.5267/j.ijiec.2021.12.003",
  issn="1923-2934",
  url="http://www.growingscience.com/ijiec/Vol13/IJIEC_2021_33.pdf"
}