Energy-aware co-optimization of facility layout and AGV configuration in intelligent manufacturing cells

Le résumé fourni par la source

In order to meet the market demands for customization and rapid response while controlling carbon emissions in manufacturing systems, it has become increasingly important to consider the collaborative optimization of equipment layout in smart production units alongside intelligent storage and transportation systems. This study investigates the loop layout problem of smart manufacturing units equipped with Automated Guided Vehicles (AGVs) through a novel simulation-optimization framework integrating intelligent search algorithms with directed graph-based isomorphism detection. An optimization model is presented with the objective functions of maximizing production capacity and minimizing energy consumption, constrained by performance indicators such as relative position of the equipment within the unit, AGV transport speeds and buffer capacity. Given the lack of a closed mathematical expression for this multi-objective function, a second-generation NSGA-II based on simulation is designed to solve the model. Furthermore, a method based on directed graph isomorphic layout processing is proposed to quickly eliminate similar solutions, enhancing solution quality and algorithm efficiency. Through comparative experimental design and practical applications in intelligent workshops, the effectiveness, superiority, and application value of this optimization algorithm in addressing the circular layout problem of smart production units are validated.

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