Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm

Mohammad Fathian (), Javid Jouzdani (), Mehdi Heydari () and Ahmad Makui ()
Additional contact information
Mohammad Fathian: Iran University of Science and Technology
Javid Jouzdani: Iran University of Science and Technology
Mehdi Heydari: Iran University of Science and Technology
Ahmad Makui: Iran University of Science and Technology

Journal of Intelligent Manufacturing, 2018, vol. 29, issue 7, No 3, 1447-1464

Abstract: Abstract Supply chain decision makers are constantly trying to improve the customer demand fulfillment process and reduce the associated costs via decision making models and techniques. As two of the most important parameters in a supply chain, supply and demand quantities are subject to uncertainty in many real-world situations. In addition, in recent decades, there is a trend to think of the impacts of supply chain design and strategies on society and environment. Especially, transportation of goods not only imposes costs to businesses but also has socioeconomic influences. In this paper, a fuzzy nonlinear programming model for supply chain design and planning under supply/demand uncertainty and traffic congestion is proposed and a hybrid meta-heuristic algorithm, based on electromagnetism-like algorithm and simulated annealing concepts, is designed to solve the model. The merit of this paper is presenting a realistic model of current issues in supply chain design and an efficient solution method to the problem. These are significant findings of this research which can be interesting to both researchers and practitioners. Several numerical examples are provided to justify the model and the proposed solution approach.

Keywords: Supply chain design; Electromagnetism-like algorithm; Demand uncertainty; Supply Uncertainty; Traffic congestion (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10845-015-1191-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:29:y:2018:i:7:d:10.1007_s10845-015-1191-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-015-1191-9

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().