Abstract
In recent years, a plethora of multi-objective evolutionary algorithms (MOEAs) have been proposed which are able to effectively handle complex multi-objective problems. In this paper, we focus on Equilibrium Problems with Equilibrium Constraints. We show that one interpretation of the game can also be handled by MOEAs and then discuss a simple methodology to map the non-cooperative outcome to the cooperative outcome. We demonstrate our proposed methodology with examples sourced from the economics and transportation systems management literature. In doing so we suggest resulting policy implications which will be of importance to regulatory authorities.
The author is grateful for financial support by the Engineering and Physical Sciences Research Council of the UK under Grant EP/H021345/1.
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Notes
- 1.
E.g. a Special Session on Bilevel Optimization was convened at the 2012 IEEE Congress on Evolutionary Computation (CEC) (June 10–15) in Brisbane, Australia.
- 2.
Recall that this is the case where we assumed that the leaders cooperated.
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Koh, A. (2014). Cooperative and Non-cooperative Equilibrium Problems with Equilibrium Constraints: Applications in Economics and Transportation. In: Snášel, V., Krömer, P., Köppen, M., Schaefer, G. (eds) Soft Computing in Industrial Applications. Advances in Intelligent Systems and Computing, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-319-00930-8_3
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