{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:46:20Z","timestamp":1760147180081,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T00:00:00Z","timestamp":1673568000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangxi Natural Science Foundation","award":["2020GXNSFAA159143","12161027"],"award-info":[{"award-number":["2020GXNSFAA159143","12161027"]}]},{"name":"Natural Science Foundation of China","award":["2020GXNSFAA159143","12161027"],"award-info":[{"award-number":["2020GXNSFAA159143","12161027"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In this paper, we present a smoothing modulus-based iterative method for solving the stochastic mixed complementarity problems (SMCP). The main idea is that we firstly transform the expected value model of SMCP into an equivalent nonsmooth system of equations, then obtain an approximation smooth system of equations by using a smoothing function, and finally solve it by the Newton method. We give the convergence analysis, and the numerical results show the effectiveness of the new method for solving the SMCP with symmetry coefficient matrices.<\/jats:p>","DOI":"10.3390\/sym15010229","type":"journal-article","created":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T04:02:04Z","timestamp":1673582524000},"page":"229","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Class of Smoothing Modulus-Based Iterative Methods for Solving the Stochastic Mixed Complementarity Problems"],"prefix":"10.3390","volume":"15","author":[{"given":"Cong","family":"Guo","sequence":"first","affiliation":[{"name":"School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingling","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mathematics Teaching and Research, Guilin Institute of Information Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenliang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,13]]},"reference":[{"key":"ref_1","first-page":"3","article-title":"Convex expected residual models for stochastic affine varitional inequality problem","volume":"6","author":"Agdeppa","year":"2010","journal-title":"Pac. 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