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- Title
Multi-task evolutionary optimization of multi-echelon location routing problems via a hierarchical fuzzy graph.
- Authors
Yan, Xueming; Jin, Yaochu; Ke, Xiaohua; Hao, Zhifeng
- Abstract
Multi-echelon location-routing problems (ME-LRPs) deal with determining the location of facilities and the routes of vehicles on multi-echelon routing tasks. Since the assignment relationship in multi-echelon routing tasks is uncertain and varying, ME-LRPs are very challenging to solve, especially when the number of the echelons increases. In this study, the ME-LRP is formulated as a hierarchical fuzzy graph, in which high-order fuzzy sets are constructed to represent the uncertain assignment relationship as different routing tasks and cross-task operators are used for routing task selection. Then, an evolutionary multi-tasking optimization algorithm is designed to simultaneously solve the multiple routing tasks. To alleviate negative transfer between the different routing tasks, multi-echelon assignment information is considered together with associated routing task selection in multi-tasking evolution optimization. The experimental results on multi-echelon routing benchmark problems demonstrate the competitiveness of the proposed method.
- Subjects
EVOLUTIONARY algorithms; LOCATION problems (Programming); FUZZY graphs; OPTIMIZATION algorithms; BENCHMARK problems (Computer science); FUZZY sets
- Publication
Complex & Intelligent Systems, 2023, Vol 9, Issue 6, p6845
- ISSN
2199-4536
- Publication type
Article
- DOI
10.1007/s40747-023-01109-0