Benders decomposition-based particle swarm optimization for competitive supply networks with a sustainable multi-agent platform and virtual alliances

Abstract

The involvement of competition in supply networks has changed the existing monopoly platform in different fields. This paper examines a multi-level decision-making framework within a triple-stage strategic approach in competitive supply networks. The various levels of these supply networks consist of parent firms (parent brands), manufacturing plants, state-owned logistics company and franchised sales centers. The parent brands, while following the strategies of the state logistics company (as the leader of the game), seek to further expand their market share in the production, supply and sales sectors. The main contributions of the proposed approach are: the existence of partnership and non-partnership synergies in different stages of planning, the emergence and development of supply networks based on downstream alliances, the design of a multi-agent distribution mechanism based on environmental sustainability requirements, and the simultaneous development of cooperation and competition in terms of virtual alliances. Further, given the features of the issue under discussion, a hybrid Benders Decomposition-Particle Swarm Optimization algorithm is utilized. The designed structure of the algorithm helps to facilitate high-dimensional problem-solving while also addressing the interactive requirements of competitive games. The results of comparing the proposed solution approach with a game-theoretical heuristic, pure Benders decomposition and bi-level sub-population genetic algorithm prove its better performance, especially in large-size instances.