Multi-supplier and multi-product with stochastic demand and constraints using genetic algorithm


This study addresses supplier selection model with multi-product, stochastic demand and constraints of service level and budget. Recently much attention is focused on the stochastic demand due to uncertainty in the real world. There are conflicting objectives such as profit, service level and resource utilization. Pareto optimal solutions and return on investment (ROI) are analyzed to provide decision maker alternative options of proper budget and service level. Genetic algorithm (GA) is used to solve this problem. The relationship between the expected profit and experimental trials is derived to test the state of convergence. The relationship between the expected profit and parameters of mutation and crossover rates is also investigated to identify a better parameter value to run GA efficiently.