Development of Discrete Artificial Electric Field Algorithm for Quadratic Assignment Problems

Anita, Anupam Yadav, Nitin Kumar, Joong Hoon Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Quadratic Assignment Problem (QAP) is a problem of facility locations of individual resources. QAP is a proven NP-hard challenging optimization problem and has a large number of real-life applications in diverse fields such as hospital layout problems, machine scheduling, keyboard design, and backboard wiring problem. Artificial electric field optimization (AEFA) is a new metaheuristic optimization algorithm and has achieved great success in continuous optimization problems. This paper presents a discrete artificial electric field algorithm for QAP. Due to the combinatorial nature of QAP, the general operations of AEFA such as particle representations, velocity and position update rules, and subtraction operations are modified. The proposed algorithm is applied to solve the QAP instances taken from the QAP library. The results show the promising performance of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of 6th International Conference on Harmony Search, Soft Computing and Applications - ICHSA 2020
EditorsSinan Melih Nigdeli, Gebrail Bekdas, Joong Hoon Kim, Anupam Yadav
PublisherSpringer Science and Business Media Deutschland GmbH
Pages411-421
Number of pages11
ISBN (Print)9789811586026
DOIs
Publication statusPublished - 2021
Event6th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2020 - Istanbul, Turkey
Duration: 2020 Apr 222020 Apr 24

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1275
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference6th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2020
Country/TerritoryTurkey
CityIstanbul
Period20/4/2220/4/24

Keywords

  • AEFA algorithm
  • Quadratic assignment problem
  • Soft computing optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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