
	Journal of Applied Sciences
	Year: 2013 \| Volume: 13 \| Issue: 6 \| Page No.: 919-923 DOI: 10.3923/jas.2013.919.923

Local Search Heuristics for the One Dimensional Bin Packing Problems

Masri Ayob, Mohd Zakree Ahmad Nazri and Yang Xiao Fei

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.

PDF Fulltext XML References Citation Report Citation

How to cite this article:

Masri Ayob, Mohd Zakree Ahmad Nazri and Yang Xiao Fei, 2013. Local Search Heuristics for the One Dimensional Bin Packing Problems. Journal of Applied Sciences, 13: 919-923.

DOI: 10.3923/jas.2013.919.923

URL: https://scialert.net/abstract/?doi=jas.2013.919.923

COMMENT ON THIS PAPER

Navigation


		Online First
		Current Issue
		Previous Issues
		Editorial Board
		Submit a Manuscript
		Guide to Authors
		Subscribe to E-alerts

Indexed In


		AGRIS
		ASCI-Database
		Asian Digital Library
		Chemical Abstract Services
		Google Scholar

Science Alert