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Improving postponement operation in warehouse: an intelligent pick-and-pack decision-support system
Authors:Y.K. Tse  K.H. Tan  S.L. Ting  K.L. Choy  G.T.S. Ho  S.H. Chung
Affiliation:1. The York Management School, University of York , Heslington , York , UK mike.tse@york.ac.uk;3. Nottingham University Business School , Jubilee Campus, Nottingham , UK;4. Department of Industrial and Systems Engineering , The Hong Kong Polytechnic University , Kowloon , Hong Kong
Abstract:Today, many manufacturers prefer to shift their pick-and-pack postponement operations to third-party logistics companies to lower operational cost and improve mass customisation flexibility. The type of pick-and-pack operation is complicated, as it usually involves a large number of stock keeping units and several warehouse operations. Surprisingly, in most 3PL, the complicated postponement operations are still mainly managed by an experienced warehouse manager, which is an unreliable methodology and often creates many mistakes. A hybrid intelligent system integrating Case-Based Reasoning and Fuzzy Logic is proposed to support the 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 benefit to managers as effective decision support of pick and pack planning can be provided. 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.
Keywords:intelligent systems  postponement  picks and pack operation  3PL
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