A new hybrid heuristic algorithm based on bacterial foraging optimization for the dynamic facility layout problem

TURANOĞLU B., AKKAYA G.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.98, ss.93-104, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 98
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.eswa.2018.01.011
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.93-104
  • Anahtar Kelimeler: Dynamic facility layout, Bacterial foraging optimization, Simulated annealing, Hybrid heuristic methods, UNEQUAL AREA FACILITY, GENETIC ALGORITHM, PLANT LAYOUT, GLOBAL OPTIMIZATION, SYSTEMS, SEARCH, DESIGN, PERFORMANCE, CHEMOTAXIS, STRATEGY
  • Atatürk Üniversitesi Adresli: Evet

Özet

One of the most important features of modern production is that the demand for the product is constantly changing. The problems showing demand variability in certain time periods are called dynamic facility layout problems (DFLP). The establishment of a balance between handling and moving costs is attempted with such problems. Because the DFLP are complex combinatorial optimization problems, classical optimization techniques may not always be sufficient to solve them. Furthermore, it is necessary to find a solution within a reasonable computation time. Therefore, researchers tend to use heuristic methods. In the literature, various heuristic methods, such as the genetic algorithm, tabu search and ant-colony algorithm, were used to solve the DFLP. The paper introduces the use of bacterial foraging optimization (BFO) to solve the DFLP. In this study, a new hybrid heuristic algorithm, called simulated annealing which is based on bacterial foraging optimization (SABFO), is proposed for the DFLP. Also, the parameter tuning of the SABFO is made by Taguchi method. The proposed algorithm is tested on the most-used test problems in the literature, and satisfactory results are obtained at reasonable computation times. The study is important to show how BFO that is a new heuristic approach is applied to the DFLP. (C) 2018 Elsevier Ltd. All rights reserved.