On the Application of Potter Optimization Algorithm for Solving Supply Chain Management Application
Unknown authors
Abstract
Supply Chain Management (SCM) applications represent real-world optimization tasks that require handling using appropriate optimization techniques.Metaheuristic algorithms are powerful optimization tools that are effective for solving complex optimization problems such as SCM.In this article, a new metaheuristic algorithm named Potter Optimization Algorithm (POA) is introduced to deal with optimization problems, especially in SCM applications.POA is mathematically modelled by the inspiration of the human process of pottery in two phases of exploration and exploitation.The exploration phase is designed based on mathematical modeling of making extensive changes to the clay (or other pottery materials) according to the given pattern.The exploitation phase is designed based on mathematical modelling of making precise and limited changes on the made pottery with the aim of creating more similarity to the given pattern.The effectiveness of the proposed POA approach to address real-world applications in SCM has been evaluated on sustainable lot size optimization.The optimization results show that POA has been able to provide effective solutions for sustainable lot size optimization case studies by managing exploration, exploitation, and balancing them during the search process at both global and local levels.In addition, the results obtained from the implementation of POA have been compared with the performance of twelve well-known metaheuristic algorithms.The analysis of the optimization results shows that POA has 100% superior performance compared to competing algorithms by providing better results in all ten case studies.