A hybrid search approach in production-distribution planning problem in supply chain using multi-agent systems

The production‐distribution planning is one of the most important approaches to support global optimisation in supply chain management (SCM), and should be solved within the integrated structure. The production‐distribution planning problem (PDPP) involves the determination of the best configuration regarding location, size, technology content and product range to achieve the firm's long‐term goals. On the other hand, teams of autonomous agents (ATeams), cooperating by sharing solutions through a common memory, have been proposed as a means of solving combinatorial optimisation problems. In this paper a hybrid search approach is presented using an agent‐based system by considering ATeams concept for solving the PDPP. For this purpose, three algorithms are provided to solve the PDPP: genetic algorithm (GA), tabu search (TS) and simulated annealing (SA). Then we combine these algorithms using a multi‐agent system and an integrated solution algorithm is proposed. Finally, the proposed approach is compared against LINGO software. The obtained results reveal that the use of multi‐agent system delivers better solutions to us.