Abstract
This study addresses bilevel linear multi-objective problem issues i.e the special case of bilevel linear programming problems where each decision maker has several objective functions conflicting with each other. We introduce an artificial multi-objective linear programming problem of which resolution can permit to generate the whole feasible set of the upper level decisions. Based on this result and depending if the leader can evaluate or not his preferences for his different objective functions, two approaches for obtaining Pareto- optimal solutions are presented.
Highlights
Bilevel programming problems occur in diverse applications, such as transportation, economics, ecology, engineering and others
This study addresses bilevel linear multi-objective problem issues i.e. the special case of bilevel linear programming problems where each decision maker has several objective functions conflicting with each other
Three reasons at least can explain the fact that the issue has not yet received a broad attention in the literature: the difficulty of searching and defining optimal solutions; the lower level optimization problem has a number of tradeoff optimal solutions; and it is computationally more complex than the conventional Multi-Objective Programming Problem or a bilevel Programming Problem
Summary
Bilevel programming problems occur in diverse applications, such as transportation, economics, ecology, engineering and others. We introduced an artificial multi-objective linear programming problem of which the resolution can permit to generate the whole set of feasible points of the upper level decisions. Based on this result and depending if the leader can evaluate or not his preferences for his different objective functions, two approaches for obtaining Pareto-optimal solutions are presented.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
