Application of Crayfish Optimization Algorithm for Addressing Combined Heat and Power Dispatch Problem

The Crayfish Optimization Algorithm (COA), a bio-inspired optimization approach, is presented in this paper to handle the Combined Heat and Power Dispatch (CHPD) problem with confined viable operating zones. The exploration and exploitation ability is mainly governed by the three stages known as the summer resort stage, competition stage, and foraging stage. Crayfish mostly change their location based on the temperature. Three CHPD case studies are used to validate the performance of the proposed method. Based on the findings, COA reduced generation costs by 2.14%, 2.87%, and 7.12% when compared to the prior best values obtained by CPSO and OTLBO. COA outperforms the other optimization techniques, as shown by the comparative analysis against Particle Swarm Optimization (PSO), Classical PSO (CPSO), Time-Varying Acceleration Coefficients PSO (TVAC-PSO), Teaching-Learning-Based Optimization (TLBO), and Oppositional TLBO (OLTBO). The outcomes demonstrate that COA outperforms these approaches regarding cost savings, computational efficiency, and solution accuracy.