Customizing Pareto Simulated Annealing for Multi-Objective Optimization of Control Cabinet Layout
| Autor: | Joanna Kolodziej, Sabri Pllana, Suejb Memeti |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Convection Interconnection Mathematical optimization Computer Science - Artificial Intelligence business.industry Computer science Other Computer Science (cs.OH) Pareto principle Robotics 02 engineering and technology Multi-objective optimization 020202 computer hardware & architecture Artificial Intelligence (cs.AI) Computer Science - Other Computer Science Simulated annealing 0202 electrical engineering electronic engineering information engineering Cabinet (room) 020201 artificial intelligence & image processing Configuration space Artificial intelligence business |
| Zdroj: | CSCS |
| Popis: | Determining the optimal location of control cabinet components requires the exploration of a large configuration space. For real-world control cabinets it is impractical to evaluate all possible cabinet configurations. Therefore, we need to apply methods for intelligent exploration of cabinet configuration space that enable to find a near-optimal configuration without evaluation of all possible configurations. In this paper, we describe an approach for multi-objective optimization of control cabinet layout that is based on Pareto Simulated Annealing. Optimization aims at minimizing the total wire length used for interconnection of components and the heat convection within the cabinet. We simulate heat convection to study the warm air flow within the control cabinet and determine the optimal position of components that generate heat during the operation. We evaluate and demonstrate the effectiveness of our approach empirically for various control cabinet sizes and usage scenarios. Comment: Preprint, CSCS22, (C) 2019 IEEE |
| Databáze: | OpenAIRE |
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