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Determining the optimal location of control cabinet components requires theexploration of a large configuration space. For real-world control cabinets itis impractical to evaluate all possible cabinet configurations. Therefore, weneed to apply methods for intelligent exploration of cabinet configurationspace that enable to find a near-optimal configuration without evaluation ofall possible configurations. In this paper, we describe an approach formulti-objective optimization of control cabinet layout that is based on ParetoSimulated Annealing. Optimization aims at minimizing the total wire length usedfor interconnection of components and the heat convection within the cabinet.We simulate heat convection to study the warm air flow within the controlcabinet and determine the optimal position of components that generate heatduring the operation. We evaluate and demonstrate the effectiveness of ourapproach empirically for various control cabinet sizes and usage scenarios.

Customizing Pareto Simulated Annealing for Multi-objective Optimization of Control Cabinet Layout