Incorporating dynamic cellular manufacturing into strategic supply chain design

Incorporating dynamic cellular manufacturing into strategic supply chain design For increasing the efficiency of the supply chain (SC), it is necessary to take into account the interactions and relationships between the stages of procurement of raw materials, manufacturing the products, and distributing them. An integrated framework is proposed in this paper for companies interested in meeting the demand for different products in the customer zones by establishing a number of plants and distributors at the candidate sites and in having SC design with reconfiguration capability based on changes in demand and more proper economic opportunities. For this purpose, a geographically distributed cell design is proposed for the selection of the proper location for each of the facilities and the production process of the products. A mixed integer linear programming model is presented here for the integration of the sectors for procurement, production, and distribution of the products in the SC. In light of the NP-hard class of the cell formation problem, a new algorithm titled hybrid genetic ant lion optimization (HGALO) algorithm is presented for finding the optimal or near-optimal solutions. A comparison is also made here between the proposed algorithm and the genetic algorithm (GA) for demonstration of the efficiency of the proposed algorithm. The quality of the solutions generated based on the HGALO algorithm demonstrates the capability and effectiveness of the algorithm in finding high quality solutions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Incorporating dynamic cellular manufacturing into strategic supply chain design

Loading next page...
 
/lp/springer_journal/incorporating-dynamic-cellular-manufacturing-into-strategic-supply-BtkjEF2AgU
Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-1346-2
Publisher site
See Article on Publisher Site

Abstract

For increasing the efficiency of the supply chain (SC), it is necessary to take into account the interactions and relationships between the stages of procurement of raw materials, manufacturing the products, and distributing them. An integrated framework is proposed in this paper for companies interested in meeting the demand for different products in the customer zones by establishing a number of plants and distributors at the candidate sites and in having SC design with reconfiguration capability based on changes in demand and more proper economic opportunities. For this purpose, a geographically distributed cell design is proposed for the selection of the proper location for each of the facilities and the production process of the products. A mixed integer linear programming model is presented here for the integration of the sectors for procurement, production, and distribution of the products in the SC. In light of the NP-hard class of the cell formation problem, a new algorithm titled hybrid genetic ant lion optimization (HGALO) algorithm is presented for finding the optimal or near-optimal solutions. A comparison is also made here between the proposed algorithm and the genetic algorithm (GA) for demonstration of the efficiency of the proposed algorithm. The quality of the solutions generated based on the HGALO algorithm demonstrates the capability and effectiveness of the algorithm in finding high quality solutions.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Nov 23, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off