DCM: D Number Extended Cognitive Map. Application on Location Selection in SCM

  • Lian Zhou Computer and Information Science Southwest University, Chongqing, China
  • Fuyuan Xiao


Offshore outsourcing is a widely used management technique for performing business functions with the aim of reducing labor and transportation costs. The selection of locations has a significant influence on the supply chain’s resilience and qualities, but the influence of multiple external factors on the supply chain’s performance in local places in a complex and uncertain environment has not been examined. In this study, we investigated the influence of external factors in a highly uncertain and complicated situation in which relationships between external factors and supply chain resilience are complicated. Furthermore, we proposed a novel model to select locations from a comprehensive perspective. Specifically, the fuzzy cognitive map (FCM) is utilized to simulate the dynamic influence process where the adjacency is aggregated by D numbers. The weights of different resilience capabilities are considered from the perspective of maximizing benefits by using the decision-making trial and evaluation laboratory-analytic network processes (DEMATEL-ANP) model. By comparing the distance to the ideal solutions, we selected the best alternative location. Our results differ from the general case, which reveals that the weights of different capabilities influence selections.


[1] Ali, S.; Hongqi, L.; Khan, S.U.; Zhongguo, Y.; Liping, Z. (2017. Success factors for software outsourcing partnership management: An exploratory study using systematic literature review. IEEE Access, 5, 23589-23612, 2017.

[2] Dekkers, R.(2000). Decision models for outsourcing and cor competencies in manufacturing. International Journal of Production Research, 38(17), 4085-4096, 2000.

[3] Dempster, A.P. (1967). Upper and lower probabilities induced by a multivalued mapping. The annals of mathematical statistics, 325-339, 1967.

[4] Dong, Y.; Zhang, J.; Li, Z.; Hu, Y.; Deng, Y.(2019). Combination of evidential sensor reports with distance function and belief entropy in fault diagnosis. International Journal of Computers Communications & Control, 14(3), 293-307, 2019.

[5] Fontela, E.; Gabus, A.(1976). The dematel observer, Battelle Geneva Research Center, Geneva, 1976.

[6] Gao, X.; Deng, Y. (2019). The generalization negation of probability distribution and its application in target recognition based on sensor fusion. International Journal of Distributed Sensor Networks,15(5), 381, 2019.

[7] Giret, A.; Julián, V.; Corchado, J.M.; Fernández, A.; Salido, M.A.; Tang, D.(2018). How to choose the greenest delivery plan: A framework to measure key performance indicators for sustainable urban logistics. IFIP International Conference on Advances in Production Management Systems, 181-189, 2018.

[8] Guan, X.; Liu, H.; Yi, X.; Zhao, J.(2018). The Improved Combination Rule of D Numbers and Its Application in Radiation Source Identification, Mathematical Problems in Engeneering, Article ID 6025680, 2018.

[9] Gurtu, A.; Searcy, C.; Jaber, M. (2016). Effects of offshore outsourcing on a nation. Sustainable Production and Consumption, 7, 94-105, 2016.

[10] Gylling, M.; Heikkilä, J.; Jussila, K.; Saarinen, M. (2015). Making decisions on offshore outsourcing and backshoring: A case study in the bicycle industry. International Journal of Production Economics, 162, 92-100, 2015.

[11] Han, Y.; Deng, Y.(2018). An enhanced fuzzy evidential dematel method with its application to identify critical success factors. Soft computing, 22(15), 5073-5090, 2018.

[12] Han, Y.; Deng, Y. (2018). An evidential fractal ahp target recognition method. Defence Science Journal, 68(4), 367-373, 2018.

[13] Han, Y.; Deng, Y.(2018). A hybrid intelligent model for assessment of critical Ambient intelligence, 9(6), 1933-1953, 2018.

[14] Han, Y.; Deng, Y. (2019). A novel matrix game with payoffs of maxitive belief structure, International Journal of Intelligent Systems, 34(4), 690-706

[15] Han, Y.; Deng, Y.; Cao, Z.; Lin, C.(2019). An interval-valued pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making, Neural Computing and Applications, 1-19, 2019.

[16] Lai, Y.J.; Liu, T.Y.; Hwang, C.L.(1994). Topsis for modm. European journal of operational research, 76(3), 486-500, 1994.

[17] Li, Y.; Deng, Y.(2019). TDBF: Two Dimension Belief Function. International Journal of Intelligent Systems, 34(8), 1968-1982, 2019.

[18] Lin, S.; Li, C.; Xu, F.; Liu, D.; Liu, J. (2018). Risk identification and analysis for new energy power system in China based on D numbers and decision-making trial and evaluation laboratory (DEMATEL), Journal of Cleaner Production,180, 81-96, 2018.

[19] Liu, P.; Zhang, X.(2019). A multicriteria decision-making approach with linguistic D numbers based on the Choquet integral, Cognitive Computation, 11(4), 560-575, 2019.

[20] Mo, H.; Deng, Y.(2019). An evaluation for sustainable mobility extended by D numbers, Technological and Economic Development of Economy, 25(5), 802-819, 2019.

[21] Mousavi, S.M.; Antuchevicien˙e, J.; Zavadskas, E.K.; Vahdani, B.; Hashemi, H.(2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty, Transport, 34(1), 30-40, 2019.

[22] Mukherjee, D.; Gaur, A.S.; Datta, A.(2013). Creating value through offshore outsourcing: An integrative framework, Journal of International Management, 19(4), 377-389, 2013.

[23] O'keefe, J.; Nadel, L.(1978). The hippocampus as a cognitive map, Clarendon Press, Oxford, 1978.

[24] Papageorgiou, E.; Stylios, C.; Groumpos, P.(2003). Fuzzy cognitive map learning based on nonlinear hebbian rule, Australasian Joint Conference on Artificial Intelligence, 256-268, 2003.

[25] Pereira, V.; Anderson, V.(2012). A longitudinal examination of hrm in a human resources offshoring (hro) organization operating from india. Journal of World Business, 47(2), 223- 231, 2012.

[26] Saaty, T.L.(1980). The analytic hierarchy process: planning. Priority Setting. Resource Allocation, MacGraw-Hill, New York International Book Company, 1980.

[27] Saaty, T.L.(1996). Decision making with dependence and feedback. The analytic network process, Rws Publications, 1996.

[28] Shafer, G., et al.(1976). A mathematical theory of evidence, vol. 1. Princeton university press, Princeton, 1976.

[29] Shankar, R.; Choudhary, D.; Jharkharia, S.(2018). An integrated risk assessment model: A case of sustainable freight transportation systems, Transportation Research Part D: Transport and Environment, 63, 662-676, 2018.

[30] Shukla, A.; Agarwal, P.; Rana, R.; Purohit, R.(2017). Applications of topsis algorithm on various manufacturing processes: A review. Materials Today: Proceedings, 4(4), 5320-5329, 2017.

[31] Singh, P.; Agrawal, R.(2018). A customer centric best connected channel model for heterogeneous and iot networks, Journal of Organizational and End User Computing, 30(4), 32-50, 2018.

[32] Sun, R.; Deng, Y.(2019). A new method to identify incomplete frame of discernment in evidence theory, IEEE Access, 7, 15547-15555

[33] Sun, R.; Deng, Y.(2019). A new method to determine generalized basic probability assignment in the open world, IEEE Access, 7, 52827-52835, 2019.

[34] Tsai, S.B.; Zhou, J.; Gao, Y.; Wang, J.; Li, G.; Zheng, Y.; Ren, P.; Xu, W.(2017). Combining fmea with dematel models to solve production process problems. Plos One, 12(8), e0183, 634, 2017.

[35] Yadlapalli, A.; Rahman, S.; Gunasekaran, A.(2018). Socially responsible governance mechanisms for manufacturing firms in apparel supply chains. International Journal of Production Economics, 196, 135-149, 2018.

[36] Yang, H.; Deng, Y. (2019). A bio-inspired optimal network division method, Physica A: Statistical Mechanics & Its Applications, 527, 210-219

[37] Yang, H.; Deng, Y.; Jones, J. (2018). Network division method based on cellular growth and physarum-inspired network adaptation, International Journal of Unconventional Computing, 13(6), 477-491, 2018.

[38] Yoon, K.; Hwang, C.L. (1981). Multiple attribute decision making: methods and applications, Springer-Verlag, Berlin, 1981.

[39] Yoon, K.P.; Kim, W.K.(2017). The behavioral topsis. Expert Systems with Applications, 89, 266-272, 2017.
How to Cite
ZHOU, Lian; XIAO, Fuyuan. DCM: D Number Extended Cognitive Map. Application on Location Selection in SCM. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 14, n. 5, p. 753-771, nov. 2019. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/3585>. Date accessed: 08 july 2020. doi: https://doi.org/10.15837/ijccc.2019.5.3585.


Offshore outsourcing; Supply chain resilience; Location selection; FCM; D number; DEMATEL-ANP; Multicriteria decision making