A Fuzzy Linear Programming Approach to Solve Bi-level Multi-objective Linear Programming Problems

Tunjo Perić (), Zoran Babić () and Sead Rešić ()
Additional contact information
Tunjo Perić: University of Zagreb
Zoran Babić: University of Split
Sead Rešić: University of Tuzla

A chapter in Advances in Operational Research in the Balkans, 2020, pp 125-135 from Springer

Abstract: Abstract This paper presents a new fuzzy linear programmingFuzzy linear programming approach to solve bi-level multi-objective linear programmingBi-level multi-objective linear programming problems. First, we solve all the linear programming models on a given set of constraints. After that, we determine membership functions of the objective functions and of the decision variables at the first level. Later, we determine weights for all the membership functions, and form a fuzzy linear programmingFuzzy linear programming modelModel. The solution of the model should be the best one for all decision-makers on both levels. To demonstrate the efficiency of the proposed approach, we solve a business planning problem and compare the obtained results with the ones obtained using fuzzy goal programming methodology.

Keywords: Bi-level multi-objective linear programming; Fuzzy linear programming; Production; Inventory and promotion planning (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-21990-1_8

Ordering information: This item can be ordered from
http://www.springer.com/9783030219901

DOI: 10.1007/978-3-030-21990-1_8

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().