Elite and dynamic opposite learning enhanced sine cosine algorithm for application to plat-fin heat exchangers design problem

The heat exchanger has been widely used in the energy and chemical industry and plays an irreplaceable role in the featured applications. The design of heat exchanger is a mixed integer complex optimization problem, where the efficient design significantly improves the efficiency and reduces the cost. Many intelligent methods have been developed for heat exchanger optimal design. In this paper, a novel variant of sine and cosine algorithm named EDOLSCA is proposed, enhanced by dynamic opposite learning algorithm and the elite strategy. The proposed method is tested in CEC2014 benchmark and proved to be of significant advantages over the original algorithm. The new algorithm is then validated in the plate-fin heat exchanger (PFHE) optimal design problem. The comparison results of the proposed algorithm and other algorithms prove that EDOLSCA also has demonstrated superiority in heat exchanger optimal design.

Automated summary

The heat exchanger is an indispensable device in the energy and chemical industry and plays a vital role in optimizing design. This paper proposes a novel algorithm called EDOLSCA for the optimal design of heat exchangers, and its advantages have been validated in practical applications.