Optimization of order fulfillment in distribution network problems

This paper focuses on optimization of order due date fulfillment reliability in multi-echelon distribution network problems with uncertainties present in the production lead time, transportation lead time, and due date of orders. Reliability regarding order due date fulfillment is critical in customer service, and customer retention. However, this reliability can be seriously influenced by supply chain uncertainties, which may induce tardiness in various stages throughout the supply chain. Supply chain uncertainty is inevitable, since most input values are predicted from historical data, and unexpected events may happen. Hence, a multi-criterion genetic integrative optimization methodology is developed for solving this problem. The proposed algorithm integrates genetic algorithms with analytic hierarchy process to enable multi-criterion optimization, and probabilistic analysis to capture uncertainties. The optimization involves determination of demand allocations in the network, transportation modes between facilities, and production scheduling in manufacturing plants. A hypothetical three-echelon distribution network is studied, and the computation results demonstrated the reliability of the proposed algorithms.