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- Title
混合三维 EDA 求解带二维装载约束的车辆配送与分布式 生产集成调度问题.
- Authors
孙蓉洁; 钱 斌; 胡 蓉; 张大骋; 向凤红
- Abstract
Aiming at a kind of widely existing vehicle distribution with two-dimensional loading constraints and distributed production integrated scheduling problem (VD2LDPISP), this paper establishes the problem model and proposes a hybrid three-dimensional estimation of distribution algorithm (H3DEDA) to solve it. Firstly, combining with the characteristics of each stage of the problem, a novel decoding rule is designed by using the cost balance strategy of each stage. The coding individual is decoded in stages, and the decoding individual with high quality can be determined. Secondly, the three-dimensional estimation of distribution algorithm (3DEDA) is used to learn and accumulate the block structure and location information of high-quality coding individuals in the population, and generates new coding individuals by sampling the probability model in 3DEDA, which can improve the ability of the algorithm to find high-quality solution regions in the solution space globally. Then, the hyper-heuristic local search (HHLS) is designed to enhance the local optimization capability of the algorithm. The HHLS low-level problem domain contains 16 effective neighborhood operations for coding individuals, decoding sub-individuals in distribution and production phase. It is high-level policy domain, by using the probability model learning quality neighborhood operation arrangement of information structure, and then by sampling the model to directly control the new neighborhood operation arrangement, it is conducive to in-depth search of different high-quality areas. Finally, the effectiveness of the proposed H3DEDA is verified by comparison of algorithms on different scale test problems.
- Subjects
DISTRIBUTION (Probability theory); PRODUCTION scheduling; NEIGHBORHOODS; PROBABILITY theory; ALGORITHMS
- Publication
Control Theory & Applications / Kongzhi Lilun Yu Yinyong, 2023, Vol 40, Issue 5, p903
- ISSN
1000-8152
- Publication type
Article
- DOI
10.7641/CTA.2022.11195