Clustering algorithms for consolidation of customer orders into vehicle shipments

Clustering algorithms for consolidation of customer orders into vehicle shipments

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Article ID: iaor19931082
Country: United States
Volume: 26B
Issue: 5
Start Page Number: 365
End Page Number: 379
Publication Date: Oct 1992
Journal: Transportation Research. Part B: Methodological
Authors: ,
Keywords: inventory: storage, storage
Abstract:

The consolidation of shipments into loads arises in a number of applications, including household moving, truckload trucking, rail and container operations. The capacitated clustering problem (CCP) is one of the underlying optimization problems for the efficient consolidation of customer orders to vehicle shipments. In this paper the authors develop optimization-based heuristic algorithms for the CCP, extending procedures developed by Mulvey and Beck, as well as algorithms developed by Fisher and Jaikumar, for the generalized assignment problem. In this paper, iterative methods are proposed that avoid the specification of ‘seed’ customers required by other algorithms, and which are shown to produce better solutions than existing heuristics. Lagrangian relaxations are used to develop rigorous bounds, which demonstrate the effectiveness of relatively simple heuristics.

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