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A Hybrid Algorithm for Distribution Problems
July/August 2005 (vol. 20 no. 4)
pp. 19-25
David Bredstr?, Link?ping University
Dick Carlsson, S?dra Cell
Mikael R?nnqvist, Norwegian School of Economics and Business Administration
A hybrid genetic algorithm helps solve the pulp distribution problem at a large Scandinavian pulp producer by finding ship schedules and optimal pulp deliveries that minimize distribution costs. It uses two linear programming models. One optimizes all transport flows for a given schedule; the other approximates a schedule's performance and selects the fittest one. The authors performed computational experiments using real-world data instances and compare the results with a mixed-integer-programming approach.

This article is part of a special issue on advanced heuristics in transportation and logistics.

Index Terms:
evolutionary computing and genetic algorithms, constrained optimization, supply chain optimization, linear programming
Citation:
David Bredstr?, Dick Carlsson, Mikael R?nnqvist, "A Hybrid Algorithm for Distribution Problems," IEEE Intelligent Systems, vol. 20, no. 4, pp. 19-25, July-Aug. 2005, doi:10.1109/MIS.2005.59
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