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Nash equilibria in binary strategies | ||
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Abstract | ||
-------- | ||
We propose a novel method to find Nash equilibria in games with binary decision variables | ||
by including compensation payments and incentive-compatibility constraints from non-cooperative game theory | ||
directly into an optimization framework in lieu of using first order conditions of a linearization, | ||
or relaxation of integrality conditions. | ||
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The reformulation offers a new approach to obtain and interpret dual variables to binary constraints | ||
using the benefit or loss from deviation rather than marginal relaxations. | ||
The method endogenizes the trade-off between overall (societal) efficiency | ||
and compensation payments necessary to align incentives of individual players. | ||
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The manuscript with the theoretical background of dual variables in integer programs | ||
and the mathematical explanation of our method is published | ||
in the [European Journal of Operational Research](https://doi.org/10.1016/j.ejor.2017.09.032). | ||
Preprints and working versions can be downloaded | ||
from [arXiv](http://arxiv.org/abs/1504.05894) | ||
and [OptimizationOnline](http://www.optimization-online.org/DB_HTML/2015/04/4874.html). | ||
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Content | ||
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This repository contains the GAMS codes for the numerical results for the electricity market example | ||
presented in Chapter 4 and the Appendix of the manuscript (including all data), | ||
as well as an additional illustrative example of a natural gas investment and operation game. | ||
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- ``MOPBQE_power_market_example``: | ||
A stylized electricity network with 6 nodes, 9 generations and 2 time periods | ||
to illustrate the binary equilibrium method. The results are presented in Chapter 4 of the manuscript. <br /> | ||
Data modified from Example 5.1 in | ||
Steven Gabriel, Antonio Conejo, Carlos Ruiz & Sauleh Siddiqui. | ||
"Solving discretely-constrained, Mixed Complementarity Problems with Applications in Energy", | ||
*Computers & Operations Research*, 40(5):1339-1350, 2013. | ||
[DOI: 10.1016/j.cor.2012.10.017](http://dx.doi.org/10.1016/j.cor.2012.10.017). | ||
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- ``MOPBQE_power_market_numerical_tests``: | ||
A large-scale electricity network dataset for the numerical tests | ||
presented in the Appendix of the manuscript. <br /> | ||
Data based on: | ||
H. Pandzic, Y. Dvorkin, T. Qiu, Y. Wang, and D. Kirschen. | ||
Unit Commitment under Uncertainty - GAMS Models | ||
Library of the Renewable Energy Analysis Lab (REAL) | ||
University of Washington, Seattle, USA. | ||
http://www.ee.washington.edu/research/real/gams_code.html. | ||
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- ``MOPBQE_resource_market_example``: | ||
A stylized natural gas investment and operation game to illustrate the versatility | ||
of the binary-equilibrium approach and its applicability to problems | ||
beyond the electricity sector. | ||
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Bibliography info | ||
----------------- | ||
*Please cite as:* <br /> | ||
Daniel Huppmann and Sauleh Siddiqui. | ||
"An exact solution method for binary equilibrium problems with compensation and the power market uplift problem", | ||
*European Journal of Operational Research*, 2017, | ||
[DOI: 10.1016/j.ejor.2017.09.032](https://doi.org/10.1016/j.ejor.2017.09.032). | ||
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Classification | ||
-------------- | ||
### Keywords | ||
binary Nash game, non-cooperative equilibrium, multi-objective optimisation, | ||
compensation, incentive compatibility, electricity market, power market, uplift payments | ||
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### Journal of Economic Literature Classification [JEL Codes](https://www.aeaweb.org/econlit/jelCodes.php?view=jel) | ||
C72, C61, L13, L94 | ||
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### Mathematics Subject Classification [MSC](https://cran.r-project.org/web/classifications/MSC.html) | ||
90C11, 90C46, 91B26 | ||
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Authors and Contributors | ||
------------------------ | ||
This method and the codes were developed by @danielhuppmann and @ssaul3h. | ||
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License | ||
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This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/) |
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