Joint Optimization of Multiprocess Routes and Layout for Low Entropy Flexible Facility

Area of Science:

• Manufacturing Systems Engineering
• Operations Research
• Industrial Ecology

Background:

• Facility layout is crucial for production efficiency and achieving manufacturing goals like energy saving and environmental protection.
• Traditional approaches often optimize facility layout and process routes independently, leading to suboptimal outcomes.
• The concept of low entropy development offers a new perspective for sustainable facility design.

Purpose of the Study:

• To develop a joint optimization model for facility layout and product process routes.
• To minimize total logistics costs while integrating energy saving and environmental protection principles.
• To apply the low entropy concept for evaluating and selecting facility layouts.

Main Methods:

• A joint optimization model considering the interaction between product process routes and facility layout.
• Analytic Network Process (ANP) for evaluating low entropy facility layouts.
• Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for simultaneous optimization of routes and layout.
• Integration of algorithm results with expert knowledge for qualitative indicator design.

Main Results:

• The joint optimization method significantly reduces total logistics costs compared to independent optimization.
• Simultaneous optimization using GA and PSO ensures a globally optimal solution for both process routes and facility layout.
• The study demonstrates the effectiveness of integrating quantitative optimization with qualitative expert evaluation.

Conclusions:

• Joint optimization of facility layout and process routes is superior to independent approaches for manufacturing efficiency and sustainability.
• The proposed model effectively balances logistics cost reduction with low entropy development principles.
• This research provides a robust framework for designing advanced, sustainable manufacturing facilities.