Local Search Heuristics for the One Dimensional Bin Packing Problems

Masri Ayob, Mohd Zakree Ahmad Nazri, Yang Xiao Fei

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This resaerch implements three basic local search heuristics; hill climbing (i.e., random descent), simulated annealing and multi-start simulated annealing. The aim is to investigate the performance of these heuristics compared to the state of art literatures. To achieve this, researchers use a common software interface (the HyFlex framework) that are designed to enable the development, testing and comparison of iterative general-purpose heuristic search algorithms. To evaluate the performance of these heuristics researchers test on one dimensional bin packing instances using simple move operator. The results demonstrated that hill climbing heuristic outperforms other approaches in all tested instances. This indicates that simple local search is more effective in solving one dimensional bin packing problems when the searcher is allowed to run in a short time.

Original languageEnglish
Pages (from-to)108-112
Number of pages5
JournalInternational Journal of Soft Computing
Volume8
Issue number2
DOIs
Publication statusPublished - 2013

Fingerprint

Bin Packing Problem
Bins
Simulated annealing
Local Search
Heuristics
Hill Climbing
Simulated Annealing
Multistart
Bin Packing
Heuristic Search
Testing
Descent
Heuristic algorithm
Search Algorithm
Software
Local search (optimization)
Evaluate
Operator

Keywords

  • Hill climbing
  • Hyflex
  • Multi-start simulated annealing
  • packing
  • Simulated annealing

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Modelling and Simulation

Cite this

Local Search Heuristics for the One Dimensional Bin Packing Problems. / Ayob, Masri; Ahmad Nazri, Mohd Zakree; Fei, Yang Xiao.

In: International Journal of Soft Computing, Vol. 8, No. 2, 2013, p. 108-112.

Research output: Contribution to journalArticle

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