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Conference Papers Year : 2013

A ’Lean’ Fuzzy Rule to Speed-Up a Taylor-Made Warehouse Management Process

Abstract

The minimization of the inventory storage cost and - as a consequence - optimize the storage capacity based on the Stock Keeping Unit (SKU) features is a challenging problem in operations management. In order to accomplish this objective, experienced managers make usually effective decisions based on the common sense and practical reasoning models. An approach based on fuzzy logic can be considered as a good alternative to the classical inventory control models. The purpose of this paper is to present a methodology which assigns incoming products to storage locations in storage departments/zones in order to reduce material handling cost and improve space utilization. The iterative Process Mining algorithm based on the concept of Fuzzy Logic systems set and association rules is proposed, which extracts interesting patterns in terms of fuzzy rules, from the centralized process datasets stored as quantitative values.
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hal-01485841 , version 1 (09-03-2017)

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Lapo Chirici, Kesheng Wang. A ’Lean’ Fuzzy Rule to Speed-Up a Taylor-Made Warehouse Management Process. 6th Programming Languages for Manufacturing (PROLAMAT), Oct 2013, Dresden, Germany. pp.61-72, ⟨10.1007/978-3-642-41329-2_8⟩. ⟨hal-01485841⟩
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