期刊
COMPUTERS & INDUSTRIAL ENGINEERING
卷 58, 期 3, 页码 373-381出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2009.06.012
关键词
Scheduling; Supply; Transportation; Genetic algorithm; Makespan
This study considers the scheduling of products and vehicles in a two-stage supply chain environment. The first stage contains m suppliers with different production speeds, while the second stage is composed off vehicles, each of which may have a different speed and different transport capacity. In addition, it is assumed that the various output products occupy different percentages of each vehicle's capacity. We model the situation as a mixed integer programming problem, and, to solve it, we propose a gendered genetic algorithm (GGA) that considers two different chromosomes with non-equivalent structures. Our experimental results show that GGA offers better performance than standard genetic algorithms that feature a unique chromosomal structure. In addition, we compare the GGA performance with that of the most similar problem reported to date in the literature as proposed by Chang and Lee [Chang, Y., & Lee, C. (2004). Machine scheduling with job delivery coordination. European Journal of Operational Research, 158(2), 470-487]. The experimental results from our comparisons illustrate the promising potential of the new GGA approach. (C) 2009 Elsevier Ltd. All rights reserved.
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