Publication Type

Conference Paper

Publication Date

7-2002

Abstract

In this paper, we consider a real-life supply chain optimization problem concerned with supplying a product from multiple warehouses to multiple geographically dispersed retailers. Each retailer faces a deterministic and period-dependent demand over some finite planning horizon. The demand of each retailer is satisfied by the supply from some predetermined warehouse through a fleet of vehicles which are only available within certain time windows at each period. Our goal is to identify a combined inventory and routing schedule such that the system-wide total cost over the planning horizon is minimised. This problem in essence is an amalgamation of two classical NP-hard optimizatin problems: the Dynamic Lotsizing problem and the Vehicle Routing problem. In this paper, we propose an efficient rolling horizon heuristic that combines two heuristics to solve this problem. Numerical experiment results show that our approach can achieve, on average, within 10% of the lower-bound proposed by Chan, Federgruen and Simchi-Levi (1998) for some specific instances generated from Solomon benchmarks.

Keywords

Meta-Heuristics, Planning, Scheduling, Search

Discipline

Computer Sciences | Operations and Supply Chain Management

Research Areas

Information Systems and Management

Publication

15th European Conference on Artificial Intelligence (ECAI), July 21-26, 2002, Lyon France

First Page

581

Last Page

585

ISBN

9784274905254

Publisher

IOS Press

City or Country

Lyon, France

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://frontiersinai.com/ecai/ecai2002/pdf/p0581.pdf

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