A hierarchical model for e-supply chain coordination and optimisation

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Purpose The integration of e-business and supply chain enables seamless information flow from suppliers to customer service network via the internet. It also enables better-coordinated materials flow from customer order to production, storage, distribution and delivery. The purpose of this paper is to describe the work that leads to the realisation of a hierarchical model for e-supply chain coordination and optimisation. Design/methodology/approach The model is based on an e-business information flow network in order to respond rapidly to the dynamics of e-supply chain and market. It can be used to realize management level strategies, and facilitate the planning and control of detailed operation schedules of supply chain units in an e-supply chain environment. Three main modules are discussed. They are routing and sequence optimiser (RSO) with the aid of a GA and TS-based multiple population search strategy (MPSS): supply chain virtual clustering (SCVC) based on fuzzy virtual clustering: and supply chain order scheduling (SCOS) using an agent-based distributed scheduling system. Findings These modules enable: the generation of preferred routings, transportation modes and work order plan under such constraints as customer service level, cycle time and cost: the formation of supply chain's unit-transportation-work order families using a clustering approach to down-size supply chain problems and increase computation efficiency: and the integration of scheduling with supply chain optimisation in order to facilitate the control of a supply chain with the aid of an agent-based distributed scheduling approach. Originality/value This paper proposed a hierarchical model for e-supply chain coordination and optimisation that is capable to solve large-scale problems. A MPSS using GA and TS was depicted in detail to expedite the RSO.

Original languageEnglish
Pages (from-to)7-24
Number of pages18
JournalJournal of Manufacturing Technology Management
Volume18
Issue number1
DOIs
StatePublished - 2 Jan 2007
Externally publishedYes

Keywords

  • Algorithmic languages
  • Electronic commerce
  • Supply chain management

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