International Journal of Waste Resources

Abstract

Applying Circular Economy in Municipal Waste Management by Optimal Approach of Game Theory

Gholamhossein Lari*

Today, industrial infrastructure societies are constantly changing. The presence of waste and municipal waste from industrial areas raises environmental concerns. Therefore, there is a need for new and optimal tools and methods to reduce the negative environmental and economic consequences. This research presents a new and optimal method to support industrial producers in various fields, especially food, to manage industrial waste as much as possible. The approach of this research is to provide an optimal structure of circular economics based on game theory that determines an adaptive decision structure based on fixed risk assessment and current knowledge. Adaptive decision-making structure based on game theory in the structure of the circular economy is a structural process for learning, improving understanding and finally adapting management decisions in a regular and efficient manner with the aim of reducing uncertainty during the management period. This research, by explicitly recognizing situational developments and improving decisions through learning, has great potential to meet future challenges in managing industrial risk and waste. This approach has been proposed as a way to re-evaluate risks and provide more adaptive and flexible management measures to strengthen infrastructure in the face of change. Sequential and adaptive updating of game theory is considered to reduce uncertainty and provide a decision management system. Finally, the proposed comparative decision-making method with a criterion based on a residential community as an industrial project in Tehran is shown to examine its feasibility and effectiveness in managing evolving risks. The results of this study show that changes in risk and vulnerability increase future risks for society and such risks can be managed with adaptive decision management system.

Published Date: 2021-01-20; Received Date: 2020-12-31