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A Computational Method for Obtaining Stackelberg Solutions to Noncooperative Two-Level Programming Problems through Evolutionary Multi-Agent Systems

Kosuke Kato24 Contact Information, Masatoshi Sakawa24 Contact Information, Takeshi Matsui24 Contact Information and Hidenori Ohtsuka24 Contact Information

(24)  Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyma, Higashi-Hiroshima 739-8527, Japan
Abstract
In management or public decision making, there often exist two decision makers (DMs) in the situation where one of them has the priority in decision over another. Such decision making situations are often formulated as two-level programming problems. Under the assumption that these DMs know the objective function and constraints for the other DM and do not have motivation to cooperate mutually, the Stackelberg solution is adopted as a reasonable solution. However, for even two-level linear programming problems as the simplest case, the problem solved to obtain Stackelberg solutions is a nonconvex programming problem with complex structures and is known as an NP-hard problem. In this paper, we propose an efficient approximate solution method for two-level programming problems based on an evolutionary multi-agent system.

Keywords  Two-level nonlinear programming - Stackelberg solution - evolutionary multi-agent system


Contact Information Kosuke Kato
Email: kosuke-kato@hiroshima-u.ac.jp
URL: http://www.sol.hiroshima-u.ac.jp/

Contact Information Masatoshi Sakawa
Email: sakawa@hiroshima-u.ac.jp
URL: http://www.sol.hiroshima-u.ac.jp/

Contact Information Takeshi Matsui
Email: tak-matsui@hiroshima-u.ac.jp
URL: http://www.sol.hiroshima-u.ac.jp/

Contact Information Hidenori Ohtsuka

URL: http://www.sol.hiroshima-u.ac.jp/
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