Risk-control approach for bottleneck transportation problem with randomness and fuzziness

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)663-678
Number of pages16
JournalJournal of Global Optimization
Volume60
Issue number4
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Bottleneck Problem
Transportation Problem
Fuzziness
Randomness
Objective function
Chance Constraints
Aggregation Function
Supply Chain Management
Multiobjective Programming
Profitability
Supply chain management
Exact Algorithms
Traffic Flow
Random variables
Agglomeration
Random variable
Optimise
Engineering
Optimization
Model

Keywords

  • Bottleneck transportation problem
  • Multiobjective programming problem
  • Risk-control
  • Strict algorithm

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Applied Mathematics
  • Management Science and Operations Research

Cite this

Risk-control approach for bottleneck transportation problem with randomness and fuzziness. / Hasuike, Takashi.

In: Journal of Global Optimization, Vol. 60, No. 4, 2014, p. 663-678.

Research output: Contribution to journalArticle

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