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Issue No.04 - July/August (2005 vol.20)
pp: 19-25
David Bredstr? , Link?ping University
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.<p>This article is part of a special issue on advanced heuristics in transportation and logistics.</p>
evolutionary computing and genetic algorithms, constrained optimization, supply chain optimization, linear programming
David Bredstr?, Mikael R?nnqvist, "A Hybrid Algorithm for Distribution Problems", IEEE Intelligent Systems, vol.20, no. 4, pp. 19-25, July/August 2005, doi:10.1109/MIS.2005.59
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