An Uncertain Programming Model for Manufacturing/Remanufacturing Hybrid System in Reverse Logistics Environment

Yu Juan Chen; Dong Bo Liu

doi:10.4028/www.scientific.net/AMM.288.251

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An Uncertain Programming Model for Manufacturing/Remanufacturing Hybrid System in Reverse Logistics Environment
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 288An Uncertain Programming Model for...

An Uncertain Programming Model for Manufacturing/Remanufacturing Hybrid System in Reverse Logistics Environment

Abstract:

An uncertain programming model for the manufacturing/remanufacturing hybrid system in reverse logistics environment under grey and fuzzy uncertainty was proposed. It considers the material suppliers, manufacturing plant, distribution centers, retailers, collection centers, disassembly center and remanufacturing center. The designed neural network can expedite the simulation process after trained from the input-output data generated with the proposed grey fuzzy simulation method. The improved Particle Swarm Optimization (PSO) algorithm based on the Differential Evolution (DE) algorithm is used to optimize the uncertain model. The numerical example illustrates that the cost will increase with the higher probability and credibility, and decrease with the higher return rate.

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Periodical:

Applied Mechanics and Materials (Volume 288)

Pages:

251-255

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.288.251

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Online since:

February 2013

Authors:

Yu Juan Chen, Dong Bo Liu

Keywords:

Differential Evolution (DE) Algorithm, Grey Fuzzy Simulation, Neural Network (NN), Particle Swarm Optimization Algorithm, Remanufacturing, Reverse Logistic

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