Performance Evaluation of Grey Wolf Optimizer and Symbiotic Organisms Search for Multi-level Production Planning with Adaptive Penalty

摘要

Production planning is a combinatorial optimization problem and involves a large number of semi-continuous variables and complex constraints. In this work, we propose an efficient strategy to handle the domain hole constraints and demonstrate its supremacy over the hard penalty approach used in the literature. Additionally, we employ the proposed strategy with two recently developed meta-heuristics algorithms, viz. Grey Wolf Optimizer and Symbiotic Organisms Search algorithm, to evaluate their performance for solving the production planning problem arising in the petrochemical industry.