Improving postponement operation in warehouse: An intelligent pick and pack decision support system

Y.K. Tse, K.H. Tan, S.L. Ting, K.L. Choy, G.T.S. Ho, S.H. Chung

Research output: Contribution to journalArticlepeer-review

Abstract

Today, many manufacturers prefer to shift their pick and pack postponement operations to third party logistics companies (3PL) to lower operational cost and improve mass customization flexibility. The type of pick and pack operation is complicated as it usually involves a large number of stock keeping units (SKUs) and several warehouse operations. Surprisingly, in most 3PL, the complicated postponement operations are still mainly managed by experienced warehouse manager which is unreliable and often creates many mistakes. A hybrid intelligent system integrating Case-Based Reasoning (CBR) and the Fuzzy Logic (FL) is proposed to support manager in making pick and pack postponement decisions. The system comprises a solution refining module that proposes and holds the details of past pick and pack operations. This approach will be of the benefit to managers that both the decision support and corporate memory can be provided necessarily to ensure success in the future. A case study is used to illustrate the applicability and effectiveness of the approach. Implications of the proposed approach are discussed, and suggestions for further work are outlined
Original languageEnglish
Pages (from-to)7181-7197
Number of pages17
JournalInternational Journal of Production Research
Volume50
Issue number24
Early online date31 Jan 2012
DOIs
Publication statusPublished - 15 Dec 2012

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