Name
Abstract | ||
|---|---|---|
This paper presents a decentralized negotiation protocol for cooperative economic scheduling in a supply chain environment. For this purpose we designed autonomous agents that maximize their profits by optimizing their local schedule and offer side payments to compensate other agents for lost profit or extra expense if cumulative profit is achievable. To further increase their income the agents have to apply a randomized local search heuristic to prevent the negotiation from stopping in locally optimal contracts. We show that the welfare could be increased by using a search strategy similar to Simulated Annealing. Unfortunately, a naïve application of this strategy makes the agents vulnerable to exploitation by untruthful partners. We develop and test a straightforward mechanism based on trust accounts to protect the agents against systematic exploitation. This "Trusted" Simulated Annealing mechanism fosters the agents to truthfully reveal their opportunity cost situation, which is used as the basis for the calculation of side payments. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/HICSS.2005.59 | HICSS |
Keywords | Field | DocType |
cumulative profit,search strategy,offer side payment,lost profit,randomized local search heuristic,simulated annealing mechanism,local schedule,simulated annealing,trust-based negotiation mechanism,decentralized economic scheduling,side payment,decentralized negotiation protocol,local search,protocols,supply chains,autonomous agents,design optimization,cumulant,autonomous agent,opportunity cost,system testing,profitability,supply chain,environmental economics | Simulated annealing,Autonomous agent,Heuristic,Computer science,Microeconomics,Supply chain,Local search (optimization),Negotiation,Opportunity cost,Profit (economics) | Conference |
ISSN | ISBN | Citations |
1530-1605 | 0-7695-2268-8-1 | 4 |
PageRank | References | Authors |
0.50 | 25 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tim Stockheim | 1 | 75 | 11.17 |
| Oliver Wendt | 2 | 127 | 20.98 |
| Michael Schwind | 3 | 81 | 10.71 |