A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduct...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of computational and applied mathematics Jg. 146; H. 1; S. 99 - 113
Hauptverfasser: Xu, Jiuping, Li, Jun
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.09.2002
Elsevier
Schlagworte:
(Stochastic) Multiple quadratic-linear programming
(Weakly) Efficient solution
Applied sciences
Exact sciences and technology
Interactive algorithm
Mathematical programming
Operational research and scientific management
Operational research. Management science
Portfolio selection model
(Stochastic) Multiple quadratic-linear programming
Interactive algorithm
(Weakly) Efficient solution
Portfolio selection model
Selection problem
Necessary and sufficient condition
Weight function
Optimization method
Multiobjective programming
Linear programming
Objective function
Quadratic programming
Random variable
Constrained optimization
Stochastic programming
ISSN:0377-0427, 1879-1778
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables’ expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0377-0427
1879-1778
DOI:10.1016/S0377-0427(02)00421-1