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Optimal scheduling for retrieval jobs in double-deep AS/RS by evolutionary algorithms. (English) Zbl 1432.90069

Summary: We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R) machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.

MSC:

90B35 Deterministic scheduling theory in operations research
90C59 Approximation methods and heuristics in mathematical programming
68T05 Learning and adaptive systems in artificial intelligence
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