Computing Cournot-Nash equilibria
Operations Research
An introduction to differential evolution
New ideas in optimization
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Power System Analysis and Design
Power System Analysis and Design
A Cooperative Coevolutionary Approach to Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Equilibrium problems with equilibrium constraints: stationarities, algorithms, and applications
Equilibrium problems with equilibrium constraints: stationarities, algorithms, and applications
Finding Nash Equilibrium Point of Nonlinear Non-cooperative Games Using Coevolutionary Strategies
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
Colonial Competitive Algorithm as a Tool for Nash Equilibrium Point Achievement
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
Solving multi-leader-common-follower games
Optimization Methods & Software
DEMO: differential evolution for multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Hybrid coevolutionary programming for Nash equilibrium search in games with local optima
IEEE Transactions on Evolutionary Computation
Manifolds of multi-leader Cournot equilibria
Operations Research Letters
Evolving neural networks to play checkers without relying on expert knowledge
IEEE Transactions on Neural Networks
A coevolutionary minimax algorithm for the detection of nash equilibrium
SIDE'12 Proceedings of the 2012 international conference on Swarm and Evolutionary Computation
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This paper introduces an evolutionary algorithm for the solution of a class of hierarchical (''leader-follower'') games known as Equilibrium Problems with Equilibrium Constraints (EPECs). In one manifestation of such games, players at the upper level who assume the role of leaders, are assumed to act non cooperatively to maximize individual payoffs. At the same time, each leader's payoffs are constrained not only by their competitor's actions but also by the behaviour of the followers at the lower level which manifests in the form of an equilibrium constraint. By a redefinition of the selection criteria used in evolutionary methods, the paper demonstrates that the solution for such games can be found via a simple modification to a standard evolutionary multiobjective algorithm. We give a proposed algorithm (NDEMO) and illustrate it with numerical examples drawn from both the transportation systems management literature and the electricity generation industry underlying the applicability of NDEMO in multidisciplinary contexts.