International Journal of Computational Intelligence Systems

Volume 11, Issue 1, 2018, Pages 672 - 691

A Novel Interactive Fuzzy Programming Approach for Optimization of Allied Closed-Loop Supply Chains

Authors
Ahmet Çalık1, *, ahmetcalik51@gmail.com, Nimet Yapıcı Pehlivan2, nimet@selcuk.edu.tr, Turan Paksoy3, tpaksoy@yahoo.com, Gerhard Wilhelm Weber4, gerhard.weber@put.poznan.pl
1Logistics Management, KTO Karatay University, Konya, 42020, Turkey
2Statistics, Selçuk University, Konya, 42075, Turkey
3Industrial Engineering, Selçuk University, Konya, 42075, Turkey
4Department of Applied Mathematics, Middle East Technical University, Ankara, Turkey
Chair of Marketing and Economic Engineering, Faculty of Engineering Management, Poznan University of Technology, ul. Strzelecka 11, 60-965 Poznan, Poland
*Corresponding author.
Corresponding Author
Received 16 June 2017, Accepted 16 January 2018, Available Online 31 January 2018.
DOI
10.2991/ijcis.11.1.52How to use a DOI?
Keywords
Closed-Loop Supply Chain Optimization; Interactive Fuzzy Programming; Common Sources; Multi-Level Programming; Preferred Compromise Solution
Abstract

In recent years, the relationship between companies and suppliers has changed with the continuous rise in environmental awareness and customer expectations. In order to fulfill customers’ needs, the actors in a Supply Chain (SC) network sometimes compete and sometimes cooperate with each other. In SC management, both competitive and collaborative strategies have become important and have required different points of view. In a collaborative environment, companies should strive for common targets with mutual relationship. After managers decided to share their resources, some positive effects have appeared on the companies and suppliers’ performance such as profitability, flexibility and efficiency. Consequently, many companies are willing to cooperate with each other in a SC network because of these reasons. On the other hand, Closed-Loop Supply Chain (CLSC) management has been attracting a growing interest because of increased environmental issues, government regulations and customer pressures. Based on this initiative, our paper presents a novel allied CLSC network design model with two different SCs including common suppliers and common collection centers. First, a decentralized multi-level Mixed-Integer Linear Programming (MILP) model that consists of two different levels of Decision Makers (DMs) is developed. The plants of common SCs comprise the upper-level DMs, common suppliers, common collection centers, and the logistics firm comprises the lower-level DMs. A novel Interactive Fuzzy Programming (IFP) approach using Fuzzy Analytic Hierarchy Process (AHP) is proposed to obtain a preferred compromise solution for the developed model. Through use of Fuzzy AHP in the proposed IFP approach, the DMs can identify the importance of the lower-level DMs. In order to validate the developed model and the proposed IFP approach, a numerical example is implemented. According to the obtained results, our proposed IFP method outperforms Sakawa and Nishizaki’s1 and Çalık et al.’s2 approach with respect to the satisfaction degrees of upper-level DMs for the developed CLSC model.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
672 - 691
Publication Date
2018/01/31
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.11.1.52How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Ahmet Çalık
AU  - Nimet Yapıcı Pehlivan
AU  - Turan Paksoy
AU  - Gerhard Wilhelm Weber
PY  - 2018
DA  - 2018/01/31
TI  - A Novel Interactive Fuzzy Programming Approach for Optimization of Allied Closed-Loop Supply Chains
JO  - International Journal of Computational Intelligence Systems
SP  - 672
EP  - 691
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.52
DO  - 10.2991/ijcis.11.1.52
ID  - Çalık2018
ER  -