Genetic algorithm for short-term scheduling of make-and-pack batch production process

doi:10.1016/j.cjche.2015.04.021

Abstract

Abstract: This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problemis NP-hard and the problemsize is exponentially large for a realistic-sized problem. Therefore, we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithmaveragely outperforms ant colony optimization and Tabu search with slightly longer computational time.

Key words: Genetic algorithm, Ant colony optimization, Tabu search, Batch scheduling, Make-and-pack production, Forward assignment strategy

摘要： This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problemis NP-hard and the problemsize is exponentially large for a realistic-sized problem. Therefore, we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithmaveragely outperforms ant colony optimization and Tabu search with slightly longer computational time.

关键词: Genetic algorithm, Ant colony optimization, Tabu search, Batch scheduling, Make-and-pack production, Forward assignment strategy

Wuthichai Wongthatsanekorn, Busaba Phruksaphanrat. Genetic algorithm for short-term scheduling of make-and-pack batch production process[J]. , 2015, 23(9): 1475-1483.

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