Keen competition and increasingly demanding customers have forced companies to use their resources more efficiently and to integrate production and transportation planning. In the last few years more and more researchers have also focused on this challenging problem by trying to determine the complexity of the individual problems and then developing fast and robust algorithms to solve them. This paper reviews existing literature on integrated production and distribution decisions at the tactical and operational level, where the distribution part is modelled as some variation of the well-known Vehicle Routing Problem (VRP). The focus is thereby on problems that explicitly consider deliveries to multiple clients in a less-than-truckload fashion. In terms of the production decisions we distinguish in our review between tactical and operational production problems by considering lot-sizing/capacity allocation and scheduling models, respectively.
The integration between production and distribution to minimize total elapsed time is an important issue for industries that produce products with a short lifespan. However, the literature focus on production environments with a single stage. This paper enhances the complexity of the production system of an integrated production and distribution system by considering flowshop environment decisions integrated with a vehicle routing problem decision. In this case, each order is produced in a permutation flowshop subsystem and then shipped to its destination by a capacitated vehicle, and the objective is to sequence these orders to minimize the makespan of the schedule. This paper uses two approaches to address this integrated problem: a mixed-integer formulation and an Iterated Greedy algorithm. The experimentation shows that the Iterated Greedy algorithm yields results with a 0.02% deviation from the optimal for problems with five jobs, and is a viable option to be used in practical cases due to its short computational time.
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