Bi-objective optimization problems with two decision makers: refining Pareto-optimal front for equilibrium solution
Mohammadali S. Monfared (),
Sayyed Ehsan Monabbati () and
Mahsa Mahdipour Azar ()
Additional contact information
Mohammadali S. Monfared: Alzahra University
Sayyed Ehsan Monabbati: Alzahra University
Mahsa Mahdipour Azar: Alzahra University
OR Spectrum: Quantitative Approaches in Management, 2020, vol. 42, issue 2, No 8, 567-584
Abstract:
Abstract The Pareto-optimality concept in multi-objective optimization theory is different from the Nash equilibrium concept in noncooperative game theory. When the objective holders are independent decision makers, i.e., human entities or organizations, any solution on the Pareto-optimal front is not necessarily an equilibrium point, hence not a valid solution. The solution has to be a Pareto-optimal-equilibrium (POE) point. In this paper, we convert a bi-objective optimization problem into a two-player game problem by introducing “induced games,” and we propose a new refinement method to find a POE point. We prove that at least one such POE point exists for a class of linear bi-objective optimization problems, and we develop an algorithm to find it. We discuss that the innovative approach considered in this paper is of real future interest to some industrial and social applications. One such example is also presented.
Keywords: Game theory; Bi-objective optimization; Nash equilibrium; Bi-matrix games; Pareto-optimal equilibrium (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s00291-020-00587-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:orspec:v:42:y:2020:i:2:d:10.1007_s00291-020-00587-9
Ordering information: This journal article can be ordered from
http://www.springer. ... research/journal/291
DOI: 10.1007/s00291-020-00587-9
Access Statistics for this article
OR Spectrum: Quantitative Approaches in Management is currently edited by Rainer Kolisch
More articles in OR Spectrum: Quantitative Approaches in Management from Springer, Gesellschaft für Operations Research e.V.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().