TY  - JOUR
T1  - Local Search Heuristics for the One Dimensional Bin Packing Problems
AU - Ayob, Masri AU - Nazri, Mohd Zakree Ahmad AU - Fei, Yang Xiao 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 2
SP  - 108
EP  - 112
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.108.112
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.108.112
KW  - Hill climbing
KW  -simulated annealing
KW  -multi-start simulated annealing
KW  -HyFlex
KW  -packing
AB  - 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.
ER  -