An Iterative Algorithm for the Nonlinear MC 2 Model with Variational Inequality Method

Chao Min, Feifei Fan, Zhaozhong Yang and Xiaogang Li
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Chao Min: School of Science, Southwest Petroleum University, Chengdu 610500, China
Feifei Fan: School of Science, Southwest Petroleum University, Chengdu 610500, China
Zhaozhong Yang: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China
Xiaogang Li: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China

Mathematics, 2019, vol. 7, issue 6, 1-13

Abstract: 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.

Keywords: nonlinear MC 2 models; implicit variational inequality; resolvent operator technique; iterative algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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