Title :
Flexible job shop scheduling problems by a hybrid artificial bee colony algorithm
Author :
Li, Junqing ; Pan, Quanke ; Xie, Shengxian
Author_Institution :
Sch. of Comput., Liaocheng Univ., Liaocheng, China
Abstract :
In this paper, an effective artificial bee colony (ABC) algorithm is proposed for solving the flexible job shop scheduling problems. The total flow time criterion was considered. In the proposed algorithm, tabu search (TS) heuristic is introduced to perform local search for employed bee, onlookers, and scout bees. Meanwhile, an external Pareto archive set is employed to record enough non-dominated solutions for the problem considered. Experimental results on five well-known benchmarks show the efficiency of the proposed hybrid algorithm. It is concluded that the proposed algorithm is superior to the very recent algorithms in term of both search quality and computational efficiency.
Keywords :
Pareto optimisation; job shop scheduling; search problems; Pareto archive set; computational efficiency; flexible job shop scheduling problem; hybrid artificial bee colony algorithm flow time criterion; search quality; tabu search; Algorithm design and analysis; Computers; Job shop scheduling; Minimization; Optimization; Processor scheduling; artificial bee colony; flexible job shop scheduling problem; tabu search;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949601