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- Title
Learning-based simulated annealing algorithm for unequal area facility layout problem.
- Authors
Lin, Juan; Shen, Ailing; Wu, Liangcheng; Zhong, Yiwen
- Abstract
This paper proposes a learning-based simulated annealing (LSA) algorithm to tackle the NP-hard unequal area facility layout problem (UA-FLP). The goal of UA-FLP is to optimize the material flow between facilities of different sizes to enhance manufacturing efficiency. The LSA algorithm incorporates a novel solution representation, an improved penalty function and a diverse set of neighborhood operators to refine the search space. By utilizing a reinforcement learning-based controller, LSA enables a flexible and efficient exploration through state detection and fast feedback. A two-stage greedy local search is employed to further exploit the search space and enhance solution quality. Additional features include temperature sampling generation to minimize parameter settings, a greedy initial solution production to relax infeasible restrictions. Experimental results on 16 well-known instances validate LSA's high proficiency compared to several state-of-the-art algorithms, and it exceeds 7 best-known solutions within a comparable time, particularly its excellent performance in large instances within a short execution time.
- Subjects
SIMULATED annealing; PLANT layout; GREEDY algorithms; SET functions
- Publication
Soft Computing - A Fusion of Foundations, Methodologies & Applications, 2024, Vol 28, Issue 6, p5667
- ISSN
1432-7643
- Publication type
Article
- DOI
10.1007/s00500-023-09372-6