Application of an Improved Whale Optimization Algorithm for optimal design of shell and tube heat exchanger

In many industrial applications, shell and tube heat exchangers (STHE) are the most common type of heat exchanger. The designer and users' primary goal is to keep the cost of the heat exchanger as low as possible. Traditional design processes, in addition to being time consuming, may not necessarily produce the best cost-effective solution. As a result, this research investigates the application of the Improved Whale Optimization Algorithm (IWOA) to the optimal design and cost minimization of shell and tube heat exchangers. IWOA benefits from an evolutionary operator crossover to promote the diversity of solutions while maintaining a reasonable local search behavior, which increase the performance in design by adjusting different design parameters such as length, tube outer diameter, pitch size, and baffle spacing. In addition, the proposed technique has been used to reduce the total cost of equipment, such as capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchangers. The effectiveness and accuracy of the proposed algorithm are tested using three different case studies and the results are compared with those obtained by the genetic algorithm (GA), Intelligent tuned harmony search (ITHS) algorithm, Particle swarm (PSO) optimizer, Artificial bee colony (ABC) algorithm, Biogeography-based optimization (BBO), and improved intelligent tuned harmony search algorithm (I-ITHS).