A single-vendor multi-buyer inventory model with multiple raw material and quality degradation: A case study on agri-food industry

Abstract

Managing degraded-quality materials in a supply chain with a single-vendor and multi- buyers is prevalent and critical in modern industry. This research addresses the single-vendor multi-buyer problem by incorporating multiple raw materials and quality degradation to maximize joint total profit (JTP). The proposed model utilizes the Whale Optimization Algorithm (WOA) for optimization, with empirical data derived from an agri-food industry case study in Indonesia. Experimental findings demonstrate the superior effectiveness of WOA compared to Chim optimization algorithm (ChOA), Genetic algorithm (GA), (GWO), Particle Swarm Optimization (PSO), and heuristic algorithm in solving the single-vendor multi-buyer problem. Sensitivity analysis reveals noteworthy insights: increased demand boosts total profit and production cycle efficiency, while elevated shipping costs for finished products negatively impact JTP by reducing production efficiency. Moreover, escalating quality degradation rates decrease JTP and production cycle time. This study significantly contributes to optimizing single-vendor and multi-buyer operations by addressing multiple raw materials and quality degradation, offering valuable insights into sensitivity analysis for critical factors in the agri-food industry.