scholarly journals A multiple objective programming approach to linear bilevel multi-follower programming

2019 ◽  
Vol 4 (3) ◽  
pp. 763-778
Author(s):  
Habibe Sadeghi ◽  
◽  
Fatemeh Moslemi
Keyword(s):  
Multiple Objective Programming ◽  
Programming Approach ◽  
Multiple Objective ◽  
Objective Programming

A FUZZY MULTIPLE OBJECTIVE PROGRAMMING TO DEA WITH IMPRECISE DATA

2004 ◽  
Vol 12 (05) ◽  
pp. 591-600 ◽  
Author(s):  
JING-RUNG YU ◽  
YEN-CHEN TZENG ◽  
GWO-HSHIUNG TZENG ◽  
TZU-YI YU ◽  
HER-JIUN SHEU
Keyword(s):  
Multiple Objective Programming ◽  
Programming Approach ◽  
Multiple Objective ◽  
Data Envelopment ◽  
Imprecise Data ◽  
Data Set ◽  
Discriminating Power ◽  
Exact Data ◽  
Programming Techniques ◽  
Objective Programming

A fuzzy multiple objective programming approach to data envelopment analysis (DEA) of imprecise data is proposed in this paper. The problems involving a mixture of imprecise and exact data for all decision making units (DMUs) could be resolved and the discriminating power of imprecise DEA (IDEA) is enhanced. Although Cooper et al. have developed IDEA to overcome the issues of imprecise data, the discriminating power is not satisfactory since too many efficient DMUs are derived. Chiang and Tzeng's approach using fuzzy multiple objective programming techniques is adopted to enhance the discriminating power of IDEA. The same data set of Cooper et al. is employed to illustrate the merit of our approach.

Modelling cropping decisions in a rural developing country: a multiple-objective programming approach

1995 ◽  
Vol 49 (2) ◽  
pp. 101-111 ◽  
Author(s):  
Donna J. Lee ◽  
Trace Tipton ◽  
PingSun Leung
Keyword(s):  
Developing Country ◽  
Multiple Objective Programming ◽  
Programming Approach ◽  
Multiple Objective ◽  
Objective Programming

scholarly journals Algorithmic Improvements of the KSU-STEM Method Verified on a Fund Portfolio Selection

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 262
Author(s):  
Adam Borovička
Keyword(s):  
Portfolio Selection ◽  
Investment Decision ◽  
Real Life ◽  
Multiple Objective Programming ◽  
Open Unit ◽  
Programming Approach ◽  
Multiple Objective ◽  
Step Method ◽  
Objective Programming ◽  
Fund Portfolio

The topic of this article is inspired by the problem faced by many people around the world: investment portfolio selection. Apart from the standardly used methods and approaches, non-traditional multiple objective programming methods can also be significant, providing even more efficient support for making a satisfactory investment decision. A more suitable method for this purpose seems to be a concept working with an interactive procedure through the portfolio that may gradually be adapted to the investor’s preferences. Such a method is clearly the Step Method (STEM) or the more suitable improved version KSU-STEM. This method is still burdened by partial algorithmic weaknesses or methodical aspects to think about, but not as much as the other methods. The potentially stronger application power of the KSU-STEM concept motivates its revision. Firstly, an unnecessarily negative principle to determine the basal value of the objectives is revised. Further, the fuzzy goals are specified, which leads to a reformulation of the revealed defuzzified multi-objective model. Finally, the imperfect re-setting of the weights (importance) of unsatisfactory objectives is revealed. Thus, the alternative approaches are proposed. The interventions to the algorithm are empirically verified through a real-life selection of a portfolio of the open unit trusts offered by CONSEQ Investment Management traded on the Czech capital market. This application confirms a significant supporting power of the revised multiple objective programming approach KSU-STEM in a portfolio-making process.

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