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Case Study: An Intelligent Decision-Support System
July/August 2005 (vol. 20 no. 4)
pp. 44-49
Zbigniew Michalewicz, University of Adelaide
Martin Schmidt, SolveIT Software
Matthew Michalewicz, SolveIT Software
Constantin Chiriac, SolveIT Software
The explosive growth in decision-support systems over the past 30 years has yielded numerous "intelligent" systems that have often produced less-than-stellar results. In addition to generating data that users can't immediately apply to their tasks, such systems are often static, rendering them unable to respond to the dynamic nature of both business and the larger world. In this case study, the authors describe a thorny logistical problem: recommending the best distribution for used cars among various automobile auctions. They solved this problem by combining prediction, optimization, and adaptation techniques into one integrated system that has generated impressive profits for a large auto manufacturer.

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

Index Terms:
car distribution system, logistics, prediction, optimization, transportation, decision-making software, adaptive software
Citation:
Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac, "Case Study: An Intelligent Decision-Support System," IEEE Intelligent Systems, vol. 20, no. 4, pp. 44-49, July-Aug. 2005, doi:10.1109/MIS.2005.64
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