抄録
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.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 663-678 |
| ページ数 | 16 |
| ジャーナル | Journal of Global Optimization |
| 巻 | 60 |
| 発行部数 | 4 |
| DOI | |
| 出版物ステータス | Published - 2014 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Applied Mathematics
- Management Science and Operations Research
これを引用
Risk-control approach for bottleneck transportation problem with randomness and fuzziness. / Hasuike, Takashi.
：: Journal of Global Optimization, 巻 60, 番号 4, 2014, p. 663-678.研究成果: Article
}
TY - JOUR
T1 - Risk-control approach for bottleneck transportation problem with randomness and fuzziness
AU - Hasuike, Takashi
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Bottleneck transportation problem
KW - Multiobjective programming problem
KW - Risk-control
KW - Strict algorithm
UR - http://www.scopus.com/inward/record.url?scp=84920706893&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920706893&partnerID=8YFLogxK
U2 - 10.1007/s10898-014-0208-9
DO - 10.1007/s10898-014-0208-9
M3 - Article
AN - SCOPUS:84920706893
VL - 60
SP - 663
EP - 678
JO - Journal of Global Optimization
JF - Journal of Global Optimization
SN - 0925-5001
IS - 4
ER -