In this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less than that under overtime. All buyers are independent of each other. For each buyer, the lead time demand is stochastic and the shortage during lead time is permitted. The main objective of this model is to determine the optimal production and delivery policies and the optimal overtime strategy, which minimize the joint expected annual cost of the system. Based on the genetic algorithm, we develop a solution procedure to find the optimal production, delivery, and overtime decision of this model. Computational experiments show the error rate between the objective values obtained by the proposed solution procedure and the solutions solved by the exhaustive method. The results indicate that the proposed mixed genetic algorithm is more effective and adoptable in comparison with the exhaustive method as it can be able to calculate the optimal solutions for at least 96% for the instances. Ultimately, an adequate numerical example is given to show the detailed process of the solution procedure, and sensitivity analysis of main parameters with managerial implication is discussed.
A Genetic Algorithm for an Integrated Production Policy Under Time-vary Demand and Unit Price
