References
- Buzzi, S., and Zappone, A. 2013. Potential games for energy-efficient resource allocation in multipoint-to-multipoint CDMA wireless data networks. Phys. Commun. 7:1–13.
- Chiu, Y. H., Lin, J.-C., Su, W.-N., and Liu, J.-K. 2015. An efficiency evaluation of the EU’s allocation of carbon emission allowances. Energy Sources, Part B. 10:192–200. DOI: 10.1080/15567249.2010.527900
- Manbachi, M., Parsaeifard, A., and Haghifam, M.-R. 2015. Generation expansion planning of distributed generation sources in an energy market based on Monte-Carlo simulation and game theory. Energy Sources, Part B: Econ., Planning, Policy 10:139–147. DOI: 10.1080/15567249.2010.518216
- Manbachi, M., and Haghifam, M.-R. 2015. The economical feasibility of combined heat and power systems in energy markets based on reliability, using dynamic game theory. Energy Sources, Part B: Econ., Planning, Policy 10:82–90. DOI: 10.1080/15567249.2010.525590
- Nagarajan, M., and Soˇsi´c, G. 2008. Game-theoretic analysis of cooperation among supply chain agents: Review and extensions. Eur. J. Oper. Res. 187:719–45.
- Nash, J. 1951. Non-cooperative games. Ann. Math. 54:286–95.
- Skaif, T. A., Zapata, M. G., and Bellalta, B. 2015. Game theory for energy efficiency in wireless sensor networks: Latest trends. J. Network Comput. Appl. 54:33–61.
- Woo, T.-H. 2015. Nuclear safeguard protocol (NSP) construction of energy policy in nuclear power plants (NPPs) for secure power production. Energy Sources, Part B 10:91–102. DOI: 10.1080/15567249.2010.535094
- Yucekaya, A., and Valenzuela, J. 2013. Agent-based optimization to estimate Nash equilibrium in power markets. Energy Sources, Part B: Econ., Planning, Policy 8:209–216. DOI: 10.1080/15567249.2011.578103.