T he inventory-routing problem (IRP) dates back 30 years. It can be described as the combination of vehiclerouting and inventory management problems, in which a supplier has to deliver products to a number of geographically dispersed customers, subject to side constraints. It provides integrated logistics solutions by simultaneously optimizing inventory management, vehicle routing, and delivery scheduling. Some exact algorithms and several powerful metaheuristic and matheuristic approaches have been developed for this class of problems, especially in recent years. The purpose of this article is to provide a comprehensive review of this literature, based on a new classification of the problem. We categorize IRPs with respect to their structural variants and the availability of information on customer demand.
In the Dial-a-Ride Problem (DARP) the aim is to design vehicle routes for a set of users who must be transported between given origin and destination pairs, subject to a variety of side constraints. The standard DARP objective is cost minimization. In addition to cost, the objectives considered in this paper include three terms related to quality of service. This gives rise to a multicriteria problem. The problem is solved by means of a flexible and simple metaheuristic which efficiently integrates the reference point method for multicriteria optimization within a tabu search mechanism. Extensive tests were performed on randomly generated data and on real-life data provided by a major transporter in the Montreal area. Results indicate that the algorithm can yield a rich set of non-dominated solutions. It can also be employed to determine good trade-offs between cost and quality of service.
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