A compromise solution method for the multiobjective minimum risk problem

We develop an approach which enables the decision maker to search for a compromise solution to a multiobjective stochastic linear programming (MOSLP) problem where the objective functions depend on parameters which are continuous random variables with normal multivariate distributions. The minimum-r...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Operational research Ročník 21; číslo 3; s. 1913 - 1926
Hlavní autoři: Bellahcene, Fatima, Marthon, Philippe
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
Springer
Témata:
Algorithms
Business and Management
Chebyshev approximation
Computational Intelligence
Computer Science
Continuity (mathematics)
Decision making
Linear programming
Management Science
Mathematical analysis
Multiple objective analysis
Operations Research
Operations Research/Decision Theory
Original Paper
Random variables
Nonlinear programming
Minimum-risk criterion
Multiobjective programming
Stochastic programming
Nonlnear programming
ISSN:1109-2858, 1866-1505
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:We develop an approach which enables the decision maker to search for a compromise solution to a multiobjective stochastic linear programming (MOSLP) problem where the objective functions depend on parameters which are continuous random variables with normal multivariate distributions. The minimum-risk criterion is used to transform the MOSLP problem into its corresponding deterministic equivalent which in turn is reduced to a Chebyshev problem. An algorithm based on the combined use of the bisection method and the probabilities of achieving goals is developed to obtain the optimal or epsilon optimal solution of this specific problem. An illustrated example is included in this paper to clarify the developed theory.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-019-00493-1