DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2005.59
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 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||