Article

Establishing an order allocation decision support system via learning curve model for apparel logistics

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Apparel firms confront the problem with effective order allocation among factories when conducting global logistics operations. The problem is non-deterministic polynomial-time hard and often complicated to obtain an optimal solution. This research tried to solve, by heuristic method, the problem via applying the learning curve to the capacity planning to improve the decision-making on global logistics operations. It designed a two-stage order allocation decision support system. This two-stage model includes: (1) selecting and sorting factories and (2) dynamic learning of order allocation. The results demonstrated that the system could develop the most suitable order allocation model among multiple factories and minimize the order allocation cost. This research further provided a case study to help verify the designed system applied in the global logistics operations of apparel industry. The proposed system seems to be more conforming to the real-world production and could offer a better suggestion concerning order allocation.

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Ketersediaan

Informasi Detail

Judul Seri

Journal of Industrial and Production Engineering

No. Panggil

ATC LO CHE e

Penerbit

Taiwan : Taylor and Francis., 2014

Deskripsi Fisik

13 p.

Bahasa

English

ISBN/ISSN

-

Klasifikasi

LO

Tipe Isi

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Tipe Media

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Tipe Pembawa

online resource

Edisi

Vol. 31, No. 5, 274–285

Subjek

order allocation
learning curve
apparel industry
global logistics management

Info Detail Spesifik

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Pernyataan Tanggungjawab

Ming-Kuen Chen

Versi lain/terkait

Lampiran Berkas

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