The management of supply-chain can be performed using distributed optimization based on Ant Colony Optimization (ACO), which uses the pheromone matrix as the mean to exchange information between the several subsystems. However, ACO can be replaced by the hybrid algorithm Beam-ACO, which fuses Beam-Search and ACO algorithms. This optimization method has proven to be more powerful than ACO algorithms for scheduling problems. Since both use the pheromone matrix to achieve the best solution, this work proposes the implementation of Beam-ACO in supply-chain management. Beam-ACO is used in this paper to optimize the supplying and logistic agents of a supply chain. The distribution system is optimized using the standard ACO algorithm, because Beam-ACO is not suitable for this type of optimization problems. Three different instances of supply-chains have been tested. Results show that the use of Beam-ACO improves the local and global results of the supply chain, and that the distributed optimization paradigm can be applied on supply chains where different agents are optimized by different algorithms.
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