Hybrid Complex Proportional Assessment-Multi-objective Grey Wolf Optimizer for Biodiesel Process Optimization

In this study, a hybrid COPRAS-MOGWO (Complex Proportional Assessment-Multi-Objective Grey Wolf Optimizer) optimization approach is proposed for optimizing biodiesel production. The performance of the MOGWO is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II). Optimization of biodiesel production from waste frying soybean oil through transesterification is considered as the case study to test the proposed algorithm. The research aims to minimize energy consumption and maximize reaction conversion and green chemistry balance simultaneously. Results indicate that MOGWO outperforms NSGA-II in terms of computational time and solution quality. Furthermore, the same best compromise solution (BCS) is identified by COPRAS across different weight-based scenarios. By comparing the relative performance of NSGA-II and MOGWO, this study contributes valuable insights into multi-objective optimization in biodiesel production and provides guidance for researchers and practitioners in selecting appropriate optimization algorithms to improve the efficiency and sustainability of biodiesel production processes.