Next Article in Journal
The Effect of SMED on Benefits Gained in Maquiladora Industry
Next Article in Special Issue
Analyzing Environmental Continuous Improvement for Sustainable Supply Chain Management: Focusing on Its Performance and Information Disclosure
Previous Article in Journal
Multi-Objective Scheduling of Electric Vehicles in Smart Distribution Network
Previous Article in Special Issue
Sustainability Assessment in Automotive and Electronics Supply Chains—A Set of Indicators Defined in a Multi-Stakeholder Approach
Article Menu

Export Article

Open AccessArticle
Sustainability 2016, 8(12), 1239; doi:10.3390/su8121239

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

1
Department of Industrial and Management Engineering, Hanyang University, Ansan 15588, Korea
2
School of Business Administration, College of Business and Economics, Chung-Ang University, Seoul 06974, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Ilkyeong Moon
Received: 14 October 2016 / Revised: 7 November 2016 / Accepted: 23 November 2016 / Published: 29 November 2016
(This article belongs to the Special Issue Sustainability in Supply Chain Management)
View Full-Text   |   Download PDF [3280 KB, uploaded 29 November 2016]   |  

Abstract

As a service oriented and networked model, cloud manufacturing (CM) has been proposed recently for solving a variety of manufacturing problems, including diverse requirements from customers. In CM, on-demand manufacturing services are provided by a temporary production network composed of several enterprises participating within an enterprise network. In other words, the production network is the main agent of production and a subset of an enterprise network. Therefore, it is essential to compose the enterprise network in a way that can respond to demands properly. A properly-composed enterprise network means the network can handle demands that arrive at the CM, with minimal costs, such as network composition and operation costs, such as participation contract costs, system maintenance costs, and so forth. Due to trade-offs among costs (e.g., contract cost and opportunity cost of production), it is a non-trivial problem to find the optimal network enterprise composition. In addition, this includes probabilistic constraints, such as forecasted demand. In this paper, we propose an algorithm, named the dynamic enterprise network composition algorithm (DENCA), based on a genetic algorithm to solve the enterprise network composition problem. A numerical simulation result is provided to demonstrate the performance of the proposed algorithm. View Full-Text
Keywords: enterprise network composition problem; cloud manufacturing; genetic algorithm; inventory model enterprise network composition problem; cloud manufacturing; genetic algorithm; inventory model
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ahn, G.; Park, Y.-J.; Hur, S. The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing. Sustainability 2016, 8, 1239.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top