University of Guilan Journal of Mathematical Modeling 2345-394X 9 3 2021 09 01 An efficient conjugate gradient method with strong convergence properties for non-smooth optimization 375 390 4471 10.22124/jmm.2020.16747.1452 EN Fahimeh Abdollahi Department of Mathematics, K. N. Toosi University of Technology, Tehran, Iran Masoud Fatemi Department of Mathematics, K. N. Toosi University of Technology, Tehran, Iran Journal Article 2020 06 06 In this paper, we introduce an efficient conjugate gradient method for solving nonsmooth optimization problems by using the Moreau-Yosida regularization approach. The search directions generated by our proposed procedure satisfy the sufficient descent property, and more importantly, belong to a suitable trust region.  Our proposed method is globally convergent under mild assumptions. Our numerical comparative results on a collection of test problems show the efficiency and superiority of our proposed method. We have also examined the ability and the effectiveness of our approach for solving some real-world engineering problems from image processing field. The results confirm better performance of our method. https://jmm.guilan.ac.ir/article_4471_6cf479f380e06f0783bdb615ea168c1e.pdf