Modeling of a Fuzzy Expert System for Choosing an Appropriate Supply Chain Collaboration Strategy

被引:5
作者
Sari, Kazim [1 ]
机构
[1] Beykent Univ, Ind Engn Dept, Istanbul, Turkey
关键词
Supply chain management; fuzzy expert system; vendor managed inventory; collaborative; planning; forecasting and replenishment; simulation; INFORMATION; INVENTORY; PERFORMANCE; REPLENISHMENT; CPFR; SIMULATION; INACCURACY; SELECTION; INDUSTRY;
D O I
10.1080/10798587.2017.1352258
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review of literature. Then, a simulation model of a supply chain is constructed to reveal the performance of collaborative practices under various scenarios. Thereby, it is made possible to establish fuzzy rules for the expert system. Finally, feasibility and practicability of our proposed model is verified with an illustrative case.
引用
收藏
页码:405 / 412
页数:8
相关论文
共 50 条
  • [1] Implementing a fuzzy expert system for ensuring information technology supply chain
    Shokouhyar, Sajjad
    Seifhashemi, Sudabeh
    Siadat, Hossein
    Ahmadi, Mohammad Milad
    EXPERT SYSTEMS, 2019, 36 (01)
  • [2] Modeling the barriers of supply chain collaboration
    Ramesh, A.
    Banwet, D. K.
    Shankar, R.
    JOURNAL OF MODELLING IN MANAGEMENT, 2010, 5 (02) : 176 - 193
  • [3] On an object-oriented modeling of supply chain and its operational strategy
    Yamaba, H
    Tomita, S
    PROCESS SYSTEMS ENGINEERING 2003, PTS A AND B, 2003, 15 : 660 - 665
  • [4] Generating a causal model of supply chain collaboration using the fuzzy DEMATEL technique
    Jeng, Don Jyh-Fu
    COMPUTERS & INDUSTRIAL ENGINEERING, 2015, 87 : 283 - 295
  • [5] Horizontal collaboration in a decentralised system: Indonesian blood supply chain
    Mansur, Agus
    Vanany, Iwan
    Arvitrida, Niniet Indah
    SUPPLY CHAIN FORUM, 2023, 24 (03): : 334 - 350
  • [6] MODELING (r, Q) POLICY IN A TWO-LEVEL SUPPLY CHAIN SYSTEM WITH FUZZY DEMAND
    Pirayesh, Mohammadali
    Yazdi, Mohammad Modarres
    INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2010, 18 (06) : 819 - 841
  • [7] Supply Chain Logistics Information Collaboration Strategy Based on Evolutionary Game Theory
    Zhang Zhiwen
    Xue Yujun
    Li Junxing
    Gong Limin
    Wang Long
    IEEE ACCESS, 2020, 8 : 46102 - 46120
  • [8] Modeling Supply Chain Diagnostics with Fuzzy Dynamic Bayesian Networks
    Kao, Han-Ying
    Huang, Chia-Hui
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2008, 15 (03): : 257 - 265
  • [9] Fuzzy decision modeling for supply chain management
    Wang, JT
    Shu, YF
    FUZZY SETS AND SYSTEMS, 2005, 150 (01) : 107 - 127
  • [10] A Fuzzy Inference System for Supply Chain Risk Management
    Behret, Hulya
    Oztaysi, Basar
    Kahraman, Cengiz
    PRACTICAL APPLICATIONS OF INTELLIGENT SYSTEMS, 2011, 124 : 429 - +