Research on Optimization of Manufacturing Workshop Facility Layout Based on Simulation and Genetic Algorithm

DOI: https://doi.org/10.62517/jbdc.202601213

Author(s)

Jiarong Li

Affiliation(s)

Business School, Shandong University of Technology, Zibo, Shandong, China

Abstract

With the transformation of manufacturing to lean and intelligent, the rationality of workshop facility layout directly affects the logistics cost, equipment efficiency and production capacity of enterprises. Traditional layout methods rely on empirical decision-making, which is difficult to cope with core challenges such as heavy parts, complex process coordination, and frequent dynamic disturbances in complex manufacturing environments. This paper systematically sorts out the classification, constraints and objectives of workshop layout optimization problems, reviews the application status of intelligent algorithms such as genetic algorithms, simulation annealing and simulation technologies such as Flexsim in layout optimization, and focuses on the combined optimization method combining system layout design with intelligent algorithms and simulation technology. On this basis, the main challenges faced by data quality, multi-objective conflict, algorithm generalization, and computing cost are discussed, and future research directions such as digital twins, deep reinforcement learning, and multi-workshop collaboration are prospected. The results show that the closed-loop optimization framework integrating qualitative experience, quantitative optimization and dynamic verification can effectively reduce the material handling distance, improve the equipment utilization rate and the production line balance rate, and provide a reusable methodological reference for manufacturing enterprises to reduce costs and increase efficiency.

Keywords

Workshop Facility Layout; System Layout Design; Genetic Simulation Annealing Algorithm; Flexsim Simulation; Logistics Optimization; Manufacturing Workshop

References

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