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Coordination of multi-echelon supply chain based on a co-evolutionary PSO algorithm

Coordination of multi-echelon supply chain based on a co-evolutionary PSO algorithm
Coordination of multi-echelon supply chain based on a co-evolutionary PSO algorithm
This paper focuses on the batching delivery problem with soft time windows and its impact on the demand allocation and production scheduling in manufacturing plants. It is critical to be able to provide the right goods or service at the right time in order to win customer orders. However, this can require high coordination among entities in the supply network. A mismatch of a single schedule may seriously influence the reliability of the supply network. Hence, holistically optimizing the schedule of each entity in the network to achieve greater coordination can reap significant rewards. The paper will also explore the tradeoff between high customer service levels in meeting due dates and operating cost. On-time delivery can result in high operating cost, while permitting early or tardy deliveries can reduce costs. Hence, we consider the problem of how to minimize operating costs when time windows are soft while maintaining a certain customer service level. A co-evolutionary Particle Swarm Optimization (PSO) algorithm is developed. Computational results show that soft time windows have a significant effect and that there are advantages in considering the coordination across the supply chain
CORMSIS-09-05
University of Southampton
Bennell, J.
38d924bc-c870-4641-9448-1ac8dd663a30
Wu, X.
b6ec2d37-5357-42db-a350-a73969909549
Zhou, H.
8341ffe7-8014-4a11-8d2a-c353b127b898
Bennell, J.
38d924bc-c870-4641-9448-1ac8dd663a30
Wu, X.
b6ec2d37-5357-42db-a350-a73969909549
Zhou, H.
8341ffe7-8014-4a11-8d2a-c353b127b898

Bennell, J., Wu, X. and Zhou, H. (2009) Coordination of multi-echelon supply chain based on a co-evolutionary PSO algorithm (Discussion Papers in Centre for Operational Research, Management Science and Information Systems, CORMSIS-09-05) Southampton, UK. University of Southampton

Record type: Monograph (Discussion Paper)

Abstract

This paper focuses on the batching delivery problem with soft time windows and its impact on the demand allocation and production scheduling in manufacturing plants. It is critical to be able to provide the right goods or service at the right time in order to win customer orders. However, this can require high coordination among entities in the supply network. A mismatch of a single schedule may seriously influence the reliability of the supply network. Hence, holistically optimizing the schedule of each entity in the network to achieve greater coordination can reap significant rewards. The paper will also explore the tradeoff between high customer service levels in meeting due dates and operating cost. On-time delivery can result in high operating cost, while permitting early or tardy deliveries can reduce costs. Hence, we consider the problem of how to minimize operating costs when time windows are soft while maintaining a certain customer service level. A co-evolutionary Particle Swarm Optimization (PSO) algorithm is developed. Computational results show that soft time windows have a significant effect and that there are advantages in considering the coordination across the supply chain

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Published date: 2009

Identifiers

Local EPrints ID: 71394
URI: https://eprints.soton.ac.uk/id/eprint/71394
PURE UUID: 1bc01fa4-228f-426e-b72b-d92a8e722a17

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Date deposited: 10 Feb 2010
Last modified: 19 Jul 2017 00:00

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