An enhanced heuristic algorithm with coordination evolution strategy for waste-mass minimization and heat integration network design

Abstract

The issue of clean production and energy efficiency has become a major concern, especially in the chemical and processing industries. In this paper, an enhanced optimization algorithm satisfying heat-waste minimization and waste-mass minimization is proposed. First, a nodes-based non-structural model and random walk algorithm with compulsive evolution for mass exchanger network synthesis are constructed. The optimization mode of continuous variables is analyzed after analyzing the characteristics of the mass exchange process. To enhance the optimization ability of the heuristic algorithm, a novel coordinated evolution strategy combining the dynamic operations of the walk length optimization and participating evolution probability adjustment is proposed. The proposed strategy can adjust the walk length via an instant objective function change and simultaneously controls the participating evolution of the number of units for effective coupled evolution. The quantified data show that the proposed strategy assists the algorithm in enhancing the local and global optimization abilities, with the final TACs of a benchmark aromatic plant case and phenol absorption process achieved being 125,457 $/yr and 334,696.6 $/yr, respectively. To evaluate the effectiveness of the proposed strategy, it was successfully applied in two industrial-scale cases of heat exchanger network synthesis, where the TAC of the aromatics plant case achieved was 2,892,800 $/yr while the TAC of a gasoline distillation case was 5,089,402.7 $/yr.

Keywords

• Mass exchanger network
• Heat exchanger network
• Heuristic algorithm
• Coordination evolution
• Parameter optimization
• Random walk algorithm