Local search heuristics for the one dimensional bin packing problems

Research output: Contribution to journalArticle

Abstract

This study 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, this study used a common software interface (the HyFlex frame work), that are designed to enable the development, testing and comparison of iterative general-purpose heuristic search algorithms. To evaluate the performance of these heuristics, the algorithms are tested on one dimensional bin packing instances using simple move operator. 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)919-923
Number of pages5
JournalJournal of Applied Sciences
Volume13
Issue number6
DOIs
Publication statusPublished - 2013

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Bins
Simulated annealing
Testing
Local search (optimization)

Keywords

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

ASJC Scopus subject areas

  • General

Cite this

Local search heuristics for the one dimensional bin packing problems. / Ayob, Masri; Ahmad Nazri, Mohd Zakree; Fei, Yang Xiao.

In: Journal of Applied Sciences, Vol. 13, No. 6, 2013, p. 919-923.

Research output: Contribution to journalArticle

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