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Manufacturing enterprises employ a series of production or assembly operations to manufacture products. These operations are performed in a particular sequence. It is crucial to establish the job sequence that will undergo the series of operations; this is known as the Permutation Flow Shop Scheduling (PFSS) problem. Mixed Integer Linear Programming (MILP) as a mathematical model is elaborated to address the PFSS problem subjected to jobs with release date constraints and minimize makespan. This scheduling problem belongs to the NP-hard optimization problem. Subsequently, a Genetic Algorithm (GA) approach has been designed and implemented. This GA approach proved highly effective in both computational efficiency and optimization performance.

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Mathematical Formulation and Genetic Algorithm for Permutation Flow Shop Scheduling with Release Date to Minimize Makespan

  • 会议论文

  • 发表日期：

    2025年

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  • Sachin Karadgi,
  • P. S. Hiremath

摘要

Manufacturing enterprises employ a series of production or assembly operations to manufacture products. These operations are performed in a particular sequence. It is crucial to establish the job sequence that will undergo the series of operations; this is known as the Permutation Flow Shop Scheduling (PFSS) problem. Mixed Integer Linear Programming (MILP) as a mathematical model is elaborated to address the PFSS problem subjected to jobs with release date constraints and minimize makespan. This scheduling problem belongs to the NP-hard optimization problem. Subsequently, a Genetic Algorithm (GA) approach has been designed and implemented. This GA approach proved highly effective in both computational efficiency and optimization performance.