Fuzzy sets and game theory in green supply chain : an optimization model

Alakhras, Marwan; Hussein, Mousa; Oussalah, Mourad (2019-06-23)
 
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https://doi.org/10.1007/978-3-030-22871-2_12

Alakhras, Marwan
Hussein, Mousa
Oussalah, Mourad
Springer Nature
23.06.2019

Alakhras M., Hussein M., Oussalah M. (2019) Fuzzy Sets and Game Theory in Green Supply Chain: An Optimization Model. In: Arai K., Bhatia R., Kapoor S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham

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© Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Proceedings of the 2019 Computing Conference, 16-17 July 2019, London, UK. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-22871-2_12.
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doi:https://doi.org/10.1007/978-3-030-22871-2_12
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https://urn.fi/URN:NBN:fi-fe2020042322170
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Abstract

An optimization model using fuzzy sets and game theory for three players is put forward in this wok. The decision model is influenced by customer demands in a green supply chain. The proposed model includes an empirical solution to enhance the confidence level of players to choose plausible green strategy. Initially, the strategies are formulated using the game theory as manufacturer, costumer and government, to be able to optimize the pay-off uncertainty conditions of demands, by combining computational fuzzy set with ability of sensitive analysis of related fuzzy parameters to enhance the calculations and problem solving, with presenting Nash equilibrium the problem solving part.

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