Issue No. 04 - July/August (2005 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2005.59
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.<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
D. Carlsson, D. Bredstr? and M. R?nnqvist, "A Hybrid Algorithm for Distribution Problems," in IEEE Intelligent Systems, vol. 20, no. , pp. 19-25, 2005.