An integrated production and transportation scheduling problem with order acceptance and resource allocation decisions

Abstract

In the global market competition, coordinating decisions and integrating different aspects of supply chains would help managers promote the overall performance of systems, and reduce the overall costs. The integration of production and transportation is one of the essential considerations of manufacturers to achieve more efficiency levels. In this paper, an integrated production and transportation scheduling problem is addressed. The objective is to maximize the revenue of accepted orders and to minimize the sum of delivery cost, weighted tardiness cost, and fixed cost of vehicles, by considering resource allocation and resource-dependent processing times. The problem is regarded as strong NP-Hard. A Mixed Integer Linear Programming (MILP) is proposed. Also, two meta-heuristic solution approaches, based on Adaptive Genetic Algorithm (AGA) and Tabu Search (TS) are proposed to solve this problem. The computational experiments based on small-scale and large-scale analyses are provided to assess the effects of different parameters of the problems on both optimality and solving time criteria. It is deduced that the proposed AGA has a better performance and higher efficiency, rather than the proposed TS, in terms of optimality. The results indicate the capability of the proposed algorithms in solving the real-life problems in an efficient manner.