Designing a competitive photovoltaic supply chain under uncertainty: An efficient L-shape algorithm

Abstract

Due to the special features of the photovoltaic system, it is crucial yet feasible to efficiently manage and coordinate its supply chain. In this study, a competitive photovoltaic supply chain network is devised in two phases. The first phase denominates three strategies of the game-theoretic approach to take into account the competition between the suppliers. In the second phase, the obtained results are included in a novel mixed-integer programming model as input parameters to design a photovoltaic supply chain. To increase the adaptability to real-world conditions, the parameters of the proposed model are considered to be imbued with uncertainty. Additionally, two-stage stochastic programming is exploited to withstand uncertainty. Due to the NP-Hard nature of the developed model, an L-shape method has been employed to solve it. The computational results corroborate the effectiveness of the solution approach. Eventually, sensitivity analyses are carried out to provide valuable managerial insights. The results indicated that the significance of the game theory approach in capturing strategic interaction among players in a competitive environment and the practicality of two-stage stochastic programming in addressing uncertainties in decision-making can optimally boost photovoltaic supply chain network design. Additionally, the L-shape method exhibits lower gaps than the benders decomposition algorithm and achieves better solutions within the same CPU time.