Probabilistic local search algorithms for concave cost transportation network problems

Probabilistic local search algorithms for concave cost transportation network problems

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Article ID: iaor20003068
Country: Netherlands
Volume: 117
Issue: 3
Start Page Number: 511
End Page Number: 521
Publication Date: Sep 1999
Journal: European Journal of Operational Research
Authors: ,
Keywords: programming: probabilistic, optimization: simulated annealing
Abstract:

In practice concave cost transportation problems are characterized as NP-hard, therefore cost functions are usually simplified as linear in order to facilitate problem solving. However, linear cost functions may not reflect actual operations, which generally results in decreased operational performance. This research employs the techniques of simulated annealing and threshold accepting to develop several heuristics that would efficiently solve these concave cost transportation network problems. A network generator has also been designed to generate many instances on an HP workstation to test the heuristics. The preliminary results show that these heuristics are potentially useful.

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