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

## TL;DR

This paper presents a multi-objective optimization method using Pareto Simulated Annealing to efficiently find near-optimal control cabinet layouts, minimizing wiring and heat convection without exhaustive search.

## Contribution

It introduces a novel application of Pareto Simulated Annealing for control cabinet layout optimization, considering multiple objectives simultaneously.

## Key findings

- Effective in finding near-optimal layouts for various cabinet sizes.
- Reduces total wire length and heat convection compared to baseline methods.
- Demonstrates practical applicability through empirical evaluation.

## Abstract

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.