Multi-Objective Design Optimization of Thermal Engineering Systems using Rao Algorithms

Abstract

Thermal engineering systems include devices or processes where heat transfer plays a major role, such as heat exchangers, refrigeration units, combustion engines, solar collectors, cooling systems in electronics, etc. These systems often have multiple performance objectives like minimizing energy consumption, maximizing heat transfer, reducing costs, improving efficiency and reliability, etc. Design optimization aims to determine the best configuration and parameters for these systems within physical, operational, and economical constraints. The number of objectives considered for optimization may be one or more than one. This study employs three optimization algorithms, known as Rao algorithms, to handle both constrained and unconstrained thermal system optimization problems under single- and multi-objective settings. Their multi-objective extensions-MO-Rao algorithms-are effectively utilized to solve selected two- and three-objective thermal engineering case studies. Additionally, the BHARAT decision-making method is applied to identify the best compromise solution from the set of Pareto-optimal non-dominated solutions. Because the optimization is performed on fast-evaluating RSM models, the obtained Pareto fronts can be readily integrated into intelligent energy management frameworks, where real-time operating conditions can be mapped to pre-optimized design or control configurations. Researchers and practitioners across scientific and engineering domains may find these algorithms advantageous in solving real-world, constrained, and non-convex single-, multi-objective optimization problems.