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Article
Publication date: 2 March 2015

Alp Ustundag and Aysenur Budak

Distribution network design (DND) has become an important strategic decision for supply chain managers with increasing competitive nature of the industry nowadays. The purpose of…

Abstract

Purpose

Distribution network design (DND) has become an important strategic decision for supply chain managers with increasing competitive nature of the industry nowadays. The purpose of this paper is to propose a web-based decision support system (DSS) for fuzzy distribution network optimization. For this purpose, a web-based DSS using fuzzy linear programming model is proposed to solve DND problem under uncertainty and a framework is created to optimize a distribution network.

Design/methodology/approach

In this study, the fuzziness in distribution network optimization is addressed. Fuzzy linear programming is used in a DSS to consider the uncertain and imprecise data. A web-based DSS architecture is presented. Furthermore, as an application, distribution network optimization is conducted for a company in the ceramics industry.

Findings

By using this DSS, the optimal transshipment amounts in the distribution network and the required facility and distribution centers can be determined for different fuzziness levels. In fact, for different uncertainty levels of input parameters, the planner can understand the range of optimum network planning costs. Based on the results of this study, planners will be able to decide how to develop the distribution network under uncertain demand.

Originality/value

Reviewing previous research in the related literature revealed that there are no studies presenting a web-based DSS using fuzzy linear programming model to solve this type of problems under uncertainty.

Details

Journal of Enterprise Information Management, vol. 28 no. 2
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 2 March 2015

Zahir Irani and Muhammad Kamal

196

Abstract

Details

Journal of Enterprise Information Management, vol. 28 no. 2
Type: Research Article
ISSN: 1741-0398

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