A Mathematical Negotiation Mechanism for Distributed Procurement Problems and a Hybrid Algorithm for its Solution

In this paper, a mathematical negotiation mechanism is designed to minimize the negotiators’ costs in distributed procurement problem at two echelons of an automotive supply chain. The buyer’s are cost and shortage penalty one-period contract. On other hand, suppliers intend solve multi-period, multi-product production planning their costs. Such provides alignment among suppliers’ order allocation, also supports partnership with valued by taking capacities into account. circumstance has been modeled via bi-level programming, which buyer acts as leader, individually appear followers lower level. To nonlinear programming model, hybrid algorithm combining particle swarm optimization (PSO) heuristic based on A* search proposed. embedded mixed-integer (MINLP) sub-problems for each supplier according received variable values determined PSO system particles (buyer’s request quotations (RFQs)). computational analyses have shown that proposed called PSO-A* outperforms PSO-SA PSO-Greedy algorithms.