@article{9234, abstract = {In this paper, we present two new inertial projection-type methods for solving multivalued variational inequality problems in finite-dimensional spaces. We establish the convergence of the sequence generated by these methods when the multivalued mapping associated with the problem is only required to be locally bounded without any monotonicity assumption. Furthermore, the inertial techniques that we employ in this paper are quite different from the ones used in most papers. Moreover, based on the weaker assumptions on the inertial factor in our methods, we derive several special cases of our methods. Finally, we present some experimental results to illustrate the profits that we gain by introducing the inertial extrapolation steps.}, author = {Izuchukwu, Chinedu and Shehu, Yekini}, issn = {1572-9427}, journal = {Networks and Spatial Economics}, keywords = {Computer Networks and Communications, Software, Artificial Intelligence}, number = {2}, pages = {291--323}, publisher = {Springer Nature}, title = {{New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity}}, doi = {10.1007/s11067-021-09517-w}, volume = {21}, year = {2021}, } @inproceedings{9227, abstract = {In the multiway cut problem we are given a weighted undirected graph G=(V,E) and a set T⊆V of k terminals. The goal is to find a minimum weight set of edges E′⊆E with the property that by removing E′ from G all the terminals become disconnected. In this paper we present a simple local search approximation algorithm for the multiway cut problem with approximation ratio 2−2k . We present an experimental evaluation of the performance of our local search algorithm and show that it greatly outperforms the isolation heuristic of Dalhaus et al. and it has similar performance as the much more complex algorithms of Calinescu et al., Sharma and Vondrak, and Buchbinder et al. which have the currently best known approximation ratios for this problem.}, author = {Bloch-Hansen, Andrew and Samei, Nasim and Solis-Oba, Roberto}, booktitle = {Conference on Algorithms and Discrete Applied Mathematics}, isbn = {9783030678982}, issn = {1611-3349}, location = {Rupnagar, India}, pages = {346--358}, publisher = {Springer Nature}, title = {{Experimental evaluation of a local search approximation algorithm for the multiway cut problem}}, doi = {10.1007/978-3-030-67899-9_28}, volume = {12601}, year = {2021}, } @article{8817, abstract = {The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for solving equilibrium problems in real Hilbert spaces. Weak convergence of the proposed method is obtained under the condition that the bifunction is pseudomonotone and Lipchitz continuous. Linear convergence is also given when the bifunction is strongly pseudomonotone and Lipchitz continuous. Numerical implementations and comparisons with other related inertial methods are given using test problems including a real-world application to Nash–Cournot oligopolistic electricity market equilibrium model.}, author = {Shehu, Yekini and Iyiola, Olaniyi S. and Thong, Duong Viet and Van, Nguyen Thi Cam}, issn = {1432-5217}, journal = {Mathematical Methods of Operations Research}, number = {2}, pages = {213--242}, publisher = {Springer Nature}, title = {{An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems}}, doi = {10.1007/s00186-020-00730-w}, volume = {93}, year = {2021}, } @article{9315, abstract = {We consider inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. To do these, we first obtain weak convergence analysis and nonasymptotic O(1/n) convergence rate of the inertial Krasnoselskii–Mann iteration for fixed point of nonexpansive operators in infinite dimensional real Hilbert spaces under some seemingly easy to implement conditions on the iterative parameters. One of our contributions is that the convergence analysis and rate of convergence results are obtained using conditions which appear not complicated and restrictive as assumed in other previous related results in the literature. We then show that Fermat–Weber location problem and primal–dual three-operator splitting are special cases of fixed point problem of nonexpansive mapping and consequently obtain the convergence analysis of inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. Some numerical implementations are drawn from primal–dual three-operator splitting to support the theoretical analysis.}, author = {Iyiola, Olaniyi S. and Shehu, Yekini}, issn = {1420-9012}, journal = {Results in Mathematics}, number = {2}, publisher = {Springer Nature}, title = {{New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications}}, doi = {10.1007/s00025-021-01381-x}, volume = {76}, year = {2021}, } @article{9365, abstract = {In this paper, we propose a new iterative method with alternated inertial step for solving split common null point problem in real Hilbert spaces. We obtain weak convergence of the proposed iterative algorithm. Furthermore, we introduce the notion of bounded linear regularity property for the split common null point problem and obtain the linear convergence property for the new algorithm under some mild assumptions. Finally, we provide some numerical examples to demonstrate the performance and efficiency of the proposed method.}, author = {Ogbuisi, Ferdinard U. and Shehu, Yekini and Yao, Jen Chih}, issn = {1029-4945}, journal = {Optimization}, publisher = {Taylor and Francis}, title = {{Convergence analysis of new inertial method for the split common null point problem}}, doi = {10.1080/02331934.2021.1914035}, year = {2021}, } @article{8196, abstract = {This paper aims to obtain a strong convergence result for a Douglas–Rachford splitting method with inertial extrapolation step for finding a zero of the sum of two set-valued maximal monotone operators without any further assumption of uniform monotonicity on any of the involved maximal monotone operators. Furthermore, our proposed method is easy to implement and the inertial factor in our proposed method is a natural choice. Our method of proof is of independent interest. Finally, some numerical implementations are given to confirm the theoretical analysis.}, author = {Shehu, Yekini and Dong, Qiao-Li and Liu, Lu-Lu and Yao, Jen-Chih}, issn = {1573-2924}, journal = {Optimization and Engineering}, pages = {2627--2653}, publisher = {Springer Nature}, title = {{New strong convergence method for the sum of two maximal monotone operators}}, doi = {10.1007/s11081-020-09544-5}, volume = {22}, year = {2021}, } @article{7925, abstract = {In this paper, we introduce a relaxed CQ method with alternated inertial step for solving split feasibility problems. We give convergence of the sequence generated by our method under some suitable assumptions. Some numerical implementations from sparse signal and image deblurring are reported to show the efficiency of our method.}, author = {Shehu, Yekini and Gibali, Aviv}, issn = {1862-4480}, journal = {Optimization Letters}, pages = {2109--2126}, publisher = {Springer Nature}, title = {{New inertial relaxed method for solving split feasibilities}}, doi = {10.1007/s11590-020-01603-1}, volume = {15}, year = {2021}, } @article{6593, abstract = {We consider the monotone variational inequality problem in a Hilbert space and describe a projection-type method with inertial terms under the following properties: (a) The method generates a strongly convergent iteration sequence; (b) The method requires, at each iteration, only one projection onto the feasible set and two evaluations of the operator; (c) The method is designed for variational inequality for which the underline operator is monotone and uniformly continuous; (d) The method includes an inertial term. The latter is also shown to speed up the convergence in our numerical results. A comparison with some related methods is given and indicates that the new method is promising.}, author = {Shehu, Yekini and Li, Xiao-Huan and Dong, Qiao-Li}, issn = {1572-9265}, journal = {Numerical Algorithms}, pages = {365--388}, publisher = {Springer Nature}, title = {{An efficient projection-type method for monotone variational inequalities in Hilbert spaces}}, doi = {10.1007/s11075-019-00758-y}, volume = {84}, year = {2020}, } @article{8077, abstract = {The projection methods with vanilla inertial extrapolation step for variational inequalities have been of interest to many authors recently due to the improved convergence speed contributed by the presence of inertial extrapolation step. However, it is discovered that these projection methods with inertial steps lose the Fejér monotonicity of the iterates with respect to the solution, which is being enjoyed by their corresponding non-inertial projection methods for variational inequalities. This lack of Fejér monotonicity makes projection methods with vanilla inertial extrapolation step for variational inequalities not to converge faster than their corresponding non-inertial projection methods at times. Also, it has recently been proved that the projection methods with vanilla inertial extrapolation step may provide convergence rates that are worse than the classical projected gradient methods for strongly convex functions. In this paper, we introduce projection methods with alternated inertial extrapolation step for solving variational inequalities. We show that the sequence of iterates generated by our methods converges weakly to a solution of the variational inequality under some appropriate conditions. The Fejér monotonicity of even subsequence is recovered in these methods and linear rate of convergence is obtained. The numerical implementations of our methods compared with some other inertial projection methods show that our method is more efficient and outperforms some of these inertial projection methods.}, author = {Shehu, Yekini and Iyiola, Olaniyi S.}, issn = {0168-9274}, journal = {Applied Numerical Mathematics}, pages = {315--337}, publisher = {Elsevier}, title = {{Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence}}, doi = {10.1016/j.apnum.2020.06.009}, volume = {157}, year = {2020}, } @article{7161, abstract = {In this paper, we introduce an inertial projection-type method with different updating strategies for solving quasi-variational inequalities with strongly monotone and Lipschitz continuous operators in real Hilbert spaces. Under standard assumptions, we establish different strong convergence results for the proposed algorithm. Primary numerical experiments demonstrate the potential applicability of our scheme compared with some related methods in the literature.}, author = {Shehu, Yekini and Gibali, Aviv and Sagratella, Simone}, issn = {1573-2878}, journal = {Journal of Optimization Theory and Applications}, pages = {877–894}, publisher = {Springer Nature}, title = {{Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces}}, doi = {10.1007/s10957-019-01616-6}, volume = {184}, year = {2020}, }