Renewable energy supply chain management with flexibility and automation in a production system

Abstract Due to technological development, there has been a rapid increase in energy demand, but the amount of available energy is not infinite. There is a daily increase in the price per unit of energy. At present, renewable energy is the option as a substitute for traditional energy. Based on this premise, this study introduces an energy supply chain management, where renewable energy can be converted from waste. The significant benefit of this system is that the utilization of waste can mitigate environmental pollution and provide a primary renewable energy source. This way, almost all traditional energy utilized places may have the benefit of using the renewable energy with less cost as waste is the raw material. This study introduces the collection of all waste from a city and ways in which the city can generate renewable energy. The waste supplier and energy manufacturer are the two players involved in this energy supply chain. The supplier collects all waste and transfers it to the manufacturer. Based on equal an unequal power of both players, there are two cases: one case for unequal power with their own profit and the other equal power with their joint profit. The Kuhn–Tucker methodology is utilized because of inequality constraint and that the Stackelberg game theoretic approach maximizes the profit of the energy supply chain because the potentiality of the energy supply chain players may not be identical. The comparative study also provides the supply chain players with equal and unequal power. Numerical experiments prove the effectiveness of this energy supply chain. The numerical investigation finds that the profit associated with the coordination policy case is greater than that from the unequal power case. Though the equal and unequal power of supply chain players are considered, 43.05% more profit is obtained for the cooperation policy. Flexibility of production rate is found strongly dependent on the development cost for both game policy and coordination policy. The sensitivity analysis is conducted for the key parameters of the model. Fifty percentage with positive and negative direction of key parameters are verified to check the effectiveness on the profit. It gives energy selling price and scrap cost of manufacturer are the best and least parameters among all parameters.