Abstract
Solving transportation problems is essential in engineering and supply chain management, where profitability depends on optimal traffic flow. This study proposes risk-control approaches for two bottleneck transportation problems with random variables and preference levels to objective functions with risk parameters. Each proposed model is formulated as a multiobjective programming problem using robust-based optimization derived from stochastic chance constraints. Since it is impossible to obtain a transportation pattern that optimizes all objective functions, our proposed models are numerically solved by introducing an aggregation function for the multiobjective problem. An exact algorithm that performs deterministic equivalent transformations and introduces auxiliary problems is also developed.
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The author would like to sincerely thank anonymous reviewers and editors for their very valuable and constructive comments and suggestions in the earlier version of this paper. According to these comments and suggestions, the earlier version has been greatly improved.
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Hasuike, T. Risk-control approach for bottleneck transportation problem with randomness and fuzziness. J Glob Optim 60, 663–678 (2014). https://doi.org/10.1007/s10898-014-0208-9
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DOI: https://doi.org/10.1007/s10898-014-0208-9