Journal of Systems Engineering and Electronics ›› 2010, Vol. 21 ›› Issue (6): 975-980.doi: 10.3969/j.issn.1004-4132.2010.06.008

• SYSTEMS ENGINEERING • Previous Articles     Next Articles

Dynamic programming methodology for multi-criteria group decision-making under ordinal preferences

Wu Li1,*, Guanqi Guo1, Chaoyuan Yue2, and Yong Zhao2   

  1. 1. School of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang  414006, P. R. China;
    2. Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China
  • Online:2010-12-20 Published:2010-01-03

Abstract:

A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the otal nconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making (MCGDM) and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.

Key words: multi-criteria group decision-making (MCGDM), ordinal preference, minimum deviation method, dynamic programming
Cook-Seiford social selection function.