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- Title
增强分布估计算法求解低碳分布式流水线调度.
- Authors
杨晓林; 胡蓉; 钱斌; 吴丽萍
- Abstract
An enhanced estimation of distribution algorithm based on ordered relationship (OEEDA) is presented to minimize the makespan and total carbon emission for a low carbon scheduling of distributed flow shop problem (DFSP– LC). In the first stage of OEEDA, an estimation of distribution algorithm based on Bayesian statistical inference (BEDA) is utilized to perform the global search in the problem’s solution space for a certain period of time, with the purpose of finding good solutions and storing them in the non-dominated set. In the second stage of OEEDA, a four-dimensional matrix based on ordered relationship (OFDM) is proposed to effectively learn and accumulate the excellent solutions’information of ordered relationship, i.e., the information of job blocks and their corresponding positions. Then, a sampling scheme that fixes some blocks in the solution is designed to guide the global search direction more clearly. Moreover, a search method based on three kinds of Insert operator, i.e., solution-based Insert, inter-factory Insert, and intra-factory Insert, is introduced to execute a more thorough local search from the promising regions obtained by the above two stages’global search. Finally, simulations and comparisons show the efficiency of the proposed OEEDA.
- Subjects
FLOW shop scheduling; INFERENTIAL statistics; TIME measurements; CARBON; ALGORITHMS
- Publication
Control Theory & Applications / Kongzhi Lilun Yu Yinyong, 2019, Vol 35, Issue 5, p803
- ISSN
1000-8152
- Publication type
Article
- DOI
10.7641/CTA.2018.70968