Model for integrating energy relevant criteria into factory layout planning

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Due to the rising price and shortage of energy, energy efficiency has become a crucial global issue and a significant challenge for factories. It not only reduces costs but also contributes to environmental protection, making it essential to prioritize energy efficiency during the early planning phase. However, this aspect is often overlooked in factory planning. This dissertation proposes a new three-stage factory planning model that includes: (1) energy recovery network generation, (2) layout alternative generation, and (3) layout alternative evaluation and selection. Initially, an energy recovery network is established to reuse process heat, thereby reducing energy consumption. In the layout alternative generation stage, energy loss from pipes, transport performance, and space requirements are considered to create suitable layout alternatives. To tackle the multi-objective layout planning problem, a hybrid optimization algorithm combining NSGA-II with local search is developed, yielding a set of optimal solutions for decision makers to choose from based on practical situations and preferences. The evaluation and selection of layout alternatives, treated as a multi-attribute decision-making problem, is addressed using a method that combines fuzzy analytic hierarchy process (Fuzzy-AHP) and technique for order preference by similarity to ideal solution (TOPSIS). Sensitivity analysis on decision weights and product demand furth