A Computational Method for Obtaining Stackelberg Solutions to Noncooperative Two-Level Programming Problems through Evolutionary
Multi-Agent Systems
Kosuke Kato24
, Masatoshi Sakawa24
, Takeshi Matsui24
and Hidenori Ohtsuka24 
| (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
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