Manufacturing companies need to make decisions regarding the choice of suppliers providing materials and the manufacturing sites for producing the final products. This decision-making problem in a supply chain is called the procurement problem. The solution to the procurement problem mainly consists of the least cost transportation between the suppliers and the manufacturing sites, and between the manufacturing sites and the customers. This research project tackles the procurement problem when the manufacturing company uses freight companies as third party transportation. The fundamental issues addressed are: (1) minimization of bid (transportation cost) for the manufacturing company, (2) maximization of payoff to the freight companies, (3) cost-optimal and cost-reliable estimation of the task-to-vehicle assignments by the freight companies, and (4) reliable fulfillment of the orders by the drivers of the vehicles. The research seeks to develop the problem solving model, communication mechanism and the solution process by using multi-agent paradigm, game theory and stochastic programming. The approach will be to use the driver's local behavior along with travel time and service time acquired in real-time through on board sensors for determining the bottlenecks on a feasible route, and announce collaboration requests for contingencies.
This work will provide the basis for a scalable information intensive modeling and problem solving architecture for real-time procurement problem solving. Results of this research can be extended to build an integrated supply chain infrastructure (in real-time), in the e-business world.
|Effective start/end date||8/15/00 → 7/31/03|
- National Science Foundation: $112,304.00