Optimization of temperature uniformity for multi microwave source alternating heating based on superpermutation planning enhanced by Harris Hawks optimization

Abstract

For the optimization of material temperature distribution during multi-source microwave heating processes, we propose utilizing the Harris Hawks Optimization Algorithm to enhance the alternating heating strategy among multiple waveguides with superpermutations. Firstly, we innovatively introduce the concept of superpermutations to assign character weights, which subsequently correlates the alternating sequences of different waveguides. Besides, we employ Hamiltonian path planning to determine the optimal order of waveguide alternation. Then, we apply the Harris Hawks Optimization Algorithm and improve the algorithm based on microwave heating evaluation criteria to optimize the strategy for waveguide alternation and enhance search performance. At last, experimental validation involves heating SiC materials in a microwave reactor to verify the credibility of physical experiments against the simulation model used. This analysis includes assessing temperature uniformity and energy conversion efficiency during the heating process, thereby demonstrating the effectiveness of the proposed heating strategy. The experimental results indicate that temperature uniformity improved by 37.75% to 80.25%, and energy conversion efficiency increased by 7.72%.