We study an integrated production and distribution scheduling model in a supply chain. In this problem,there is a set of orders from several customers that has to be processed on a single machine located in a factory. Each order has a release date imposed by the corresponding supplier for delivering the order.In the factory, orders must be batched and routed to be delivered to the corresponding customers. We propose a bi-objective model in order to find a joint schedule of production and distribution to optimize the customers’ service level, measured as the mean delivery time and the total transportation cost. An integer linear programming model, in which a weighted sum of both objectives is converted to a single objective, is developed and solved. In addition, two local search algorithms and a metaheuristic algorithm based on tabu search are developed to solve large-scale problems at reasonable times. Moreover,two bi-objective solution methods are developed to find the Pareto solutions for the bi-objective problem. Finally, the performances of all developed solution approaches are analyzed and compared using randomly generated test sets and managerial insights are drawn from multiple numerical experiments.

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