Title :
A Novel Differential Evolution Algorithm for a Single Batch-Processing Machine with Non-Identical Job Sizes
Author :
Zhang, Wen-Gong ; Chen, Hua-Ping ; Lu, Di ; Shao, Hao
Author_Institution :
Dept. of Inf. Manage. & Decision Sci., Univ. of Sci. & Technol. of China, Hefei
Abstract :
This paper proposes a novel differential evolution algorithm approach to minimize makespan for a single batch-processing machine with non-identical job sizes. Batch processing machines can process all the jobs in a batch simultaneously. The processing times and the sizes of the jobs are known. The machine can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time of all the jobs in that batch. According to the discrete characteristic of the problem, an iterative model with new operations is designed for the proposed algorithm. It is simple to implement and is suitable for discrete problems, especially for scheduling batch-processing machine problems with non-identical job sizes. The computational results show that the proposed algorithm is effective compare to the algorithms in the literature.
Keywords :
batch processing (industrial); evolutionary computation; iterative methods; scheduling; differential evolution algorithm; iterative model; nonidentical job sizes; scheduling; single batch-processing machine; Algorithm design and analysis; Heat treatment; Heuristic algorithms; Information management; Iterative algorithms; Job shop scheduling; Machine intelligence; Metalworking machines; Processor scheduling; Semiconductor device manufacture; Batch processing machine; Makespan; Novel differential evolution algorithm; Scheduling;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.385