Optimization route arrangement: A new concept to achieve high efficiency and quality in heat exchanger network synthesis

Heuristic algorithms are widely used in the global optimization of heat exchanger network synthesis (HENS). However, since heuristic algorithms are often characterized by a divergent search and a combi-nation of multi-parameters, it is difficult to weigh and balance the global and local search in the process. In existing algorithms, the global and local search weight is commonly fixed during optimization. As a result, the algorithms hardly distribute the structural and continuous variables optimization suitably, sometimes even becoming invalid. Even more so, such algorithms fail to realize functions enhancing the searching ability. Therefore, this paper proposes a new, phased, modular concept that supports functional and sub-functional combinations to timely escape the stagnant status and obtain satisfying solutions with high efficiency and high quality. The concept's main goal is to achieve flexible combining and sequencing of different functions during the optimization process. Hence, the optimization route arrangement em-phasizes the functions' distribution, which differs from the sequential methods decomposing the whole problem. Each route's components are not unique, and the structure's current needs can change the mod-ules' sequences and categories. Such coordination of modules improves the algorithm's exploration and exploitation abilities, enabling the proposed method to attain better results within less computational time and rendering. Therefore, the proposed method is more suitable in large-scale HENS owing to much local optima involved in cases. Three cases are used to demonstrate the proposed routes' validity, which shows that the optimization route arrangement successfully decreases the total annual cost and improves computational efficiency. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Heuristic algorithms are widely used in heat exchanger network synthesis, but existing algorithms often struggle with balancing global and local search. This paper proposes a new modular concept that allows for flexible combining and sequencing of functions to improve algorithm efficiency. The proposed method demonstrates improved results in large-scale HENS.