Sustainable economic production quantity optimization (SEPQ) considering food waste emission and water waste emission using genetic algorithm

This study presents a novel approach for optimizing Sustainable Economic Production Quantity (SEPQ) by incorporating food waste and water waste emissions into the production planning process through the use of a Genetic Algorithm (GA). The objective is to minimize the environmental impacts while maximizing output volumes and decreasing total production costs. The Genetic Algorithm was utilized in a small and medium-sized firm that specializes in the multi-products food manufacturing sector. The GA was applied to systematically seek solutions that were close to optimal through 100 simulations. By implementing the optimized parameters in a case study of the SME industry, the production quantities for the two products were determined optimally with minimal total annual costs. The sensitivity analysis has shown that the SEPQ model remains strong and unaffected by changes in warehouse capacity, costs of solid waste disposal, and costs of liquid waste sales. This highlights the significance of waste management in attaining cost-effectiveness. The study offers helpful insights into the equilibrium between economic efficiency and environmental sustainability in production systems, hence contributing to the continuous advancement of sustainable manufacturing strategies.