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Soft Computing

, Volume 23, Issue 3, pp 961–986 | Cite as

Bi-objective corridor allocation problem using a permutation-based genetic algorithm hybridized with a local search technique

  • Zahnupriya Kalita
  • Dilip DattaEmail author
  • Gintaras Palubeckis
Methodologies and Application
  • 185 Downloads

Abstract

As a more practical form of the double-row layout problem, the bi-objective corridor allocation problem (bCAP) was introduced, in which a given number of facilities are to be placed on opposite sides of a central corridor so as to minimize both the overall flow cost among the facilities and the length of the corridor. Further, the bCAP seeks the placement of the facilities starting from the same level along the corridor without allowing any gap between two facilities of a row. In the initial proposal, the bCAP was solved as an unconstrained optimization problem using a permutation-based genetic algorithm (pGA). It is observed that the pGA alone is not sufficient to reach to the potential solutions of the complicated bCAP. In this work, incorporating a promising local search technique in the pGA, the hybridized pGA is found outperforming the simple pGA as well as a simulated annealing and tabu search-based approach in a number of instances of sizes 60 and above, in terms of both the best objective values and statistical analysis. Moreover, the hybridized pGA could explore multiple optimal solutions for some of such instances.

Keywords

Combinatorial optimization Corridor allocation Multi-objective optimization Genetic algorithm 

Notes

Compliance with ethical standards

Conflict of interest

All authors listed have agreed to be named as authors on this manuscript and they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Citation

Included all works (data, text, and theories) of other authors have been cited properly.

Originality

The work is original, and neither it was published previously nor it has been submitted somewhere simultaneously for publication in any form.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringTezpur UniversityNapaam, TezpurIndia
  2. 2.Faculty of InformaticsKaunas University of TechnologyKaunasLithuania

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