Integer programming formulations of discrete hub location problems

Multimodal freight transportation planning : a literature review

The inventory-routing problem (IRP) dates back 30 years. It can be described as the combination of vehicle-routing 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.

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Thirty Years of Inventory Routing

The evolution and future of manufacturing: A review

Invited Review: Industrial aspects and literature survey: Combined inventory management and routing

Hub location–allocation in intermodal logistic networks

Design of intermodal logistics networks with hub delays

This research addresses strategic planning for an interregional, hub based, intermodal logistics network operated by a logistics service provider. A tabu search meta-heuristic is used to solve a mathematical optimization model that extends the p-hub median model for interacting hub location-allocation problems to the domain of intermodal logistics. An empirical study based on a subset of US freight flows shows that intermodal logistics networks differ significantly from traditional over-the-road logistics networks in their hub locations, network structure, and their use of direct and inter-hub shipments. Furthermore, intermodal logistics networks are more sensitive to changes in service requirements and costs.

Intermodal logistics: The interplay of financial, operational and service issues

This paper examines several different policies for an inventory control problem in which the demand process is nonstationary and partially observed. The probability distribution for the demand in each period is determined by the state of a Markov chain, the core process. However, the state of this core process is not directly observed, only the actual demand is observed by the decision maker. Given this demand process, the inventory control problem is a composite-state, partially observed Markov decision process POMDP, which is an appropriate model for a number of dynamic demand problems. In practice, managers often use certainty equivalent control CEC policies to solve such a problem. However, this paper presents results that demonstrate that there are other practical control policies that almost always provide much better solutions for this problem than the CEC policies commonly used in practice. The computational results also indicate how specific problem characteristics influence the performance of each of the alternative policies.

Charles R. Sox

Papers

Hub location–allocation in intermodal logistic networks

Design of intermodal logistics networks with hub delays

Intermodal logistics: The interplay of financial, operational and service issues

Adaptive Inventory Control for Nonstationary Demand and Partial Information

A review of the stochastic lot scheduling problem