Metric-Space Negotiation for Distributed Scheduling Problems

We tackle the challenge of applying automated negotiation to self-interested agents with local but linked combinatorial optimization problems. Using distributed production scheduling problems in the context of supply chain management, we first present a negotiation protocol built on existing work in the multi-agent negotiation literature. Then, we propose two negotiation strategies for making concessions in a joint search space of agreements. The first strategy concedes on utility, an approach commonly used in the negotiation literature; the second strategy concedes in a metric space while maximizing an agent’s local utility. Experimental results show that this novel metric-space negotiation strategy outperforms its utility-based counterpart and is able to obtain close-tooptimal solutions. This paper presents the first study of applying automated negotiation to self-interested agents, each with a local combinatorial optimization problem.