DocumentCode :
478532
Title :
A Hybrid Heuristic Neighborhood Algorithm for the Job Shop Scheduling Problem
Author :
Cui, Jianshuang ; Li, Tieke
Author_Institution :
Sch. of Economic Manage., Univ. of Sci. & Technol., Beijing
Volume :
6
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
412
Lastpage :
416
Abstract :
A hybrid heuristic neighborhood algorithm (HHNA) is proposed for the job shop scheduling problem. The hybrid design is mainly composed of two iterative phases. Phase one aim at generating new scheduling solutions through the conditioned neighborhood swapping. An evaluation procedure is designed to judge the feasibility of a new solution. An infeasible solution will be discarded. Phase two is an improved critical path algorithm that is used to do the intensification search. The computational results demonstrate that the algorithm is highly efficiency both in solution quality and time. Moreover, the algorithm is simple and robust in implementation since it needs no special parameters to be adjusted with different sizes of the problems.
Keywords :
heuristic programming; job shop scheduling; conditioned neighborhood swapping; critical path algorithm; hybrid heuristic neighborhood algorithm; iterative phases; job shop scheduling problem; Approximation methods; Conference management; Dynamic scheduling; Heuristic algorithms; Iterative algorithms; Job shop scheduling; Processor scheduling; Robustness; Scheduling algorithm; Technology management; Critical path; Greedy makespan; Hybrid heuristic; Job shop scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.149
Filename :
4667869
Link To Document :
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