An Iterative Algorithm for the Nonlinear MC2 Model with Variational Inequality Method

Mathematics

Chao Min¹  Feifei Fan¹  Xiaogang Li²  Zhaozhong Yang² 

[1] School of Science, Southwest Petroleum University, Chengdu 610500, China;State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China;

关键词: nonlinear MC² models;    implicit variational inequality;    resolvent operator technique;    iterative algorithm;   

DOI  :  10.3390/math7060514

来源: DOAJ

【 摘 要 】

The multiple criteria and multiple constraint level (MC ${}^2$ ) model is a useful tool to deal with the decision programming problems, which concern multiple decision makers and uncertain resource constraint levels. In this paper, by regarding the nonlinear MC ${}^2$ problems as a class of mixed implicit variational inequalities, we develop an iterative algorithm to solve the nonlinear MC ${}^2$ problems through the resolvent operator technique. The convergence of the generated iterative sequence is analyzed and discussed by a calculation example, and the stability of Algorithm 1 is also verified by error propagation. By comparing with two other MC ${}^2$ -algorithms, Algorithm 1 performs well in terms of number of iterations and computation complexity.

【 授权许可】

Unknown