TY - CONF
AB - 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.
AU - Bloch-Hansen, Andrew
AU - Samei, Nasim
AU - Solis-Oba, Roberto
ID - 9227
SN - 0302-9743
T2 - Conference on Algorithms and Discrete Applied Mathematics
TI - Experimental evaluation of a local search approximation algorithm for the multiway cut problem
VL - 12601
ER -
TY - JOUR
AB - 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.
AU - Izuchukwu, Chinedu
AU - Shehu, Yekini
ID - 9234
JF - Networks and Spatial Economics
KW - Computer Networks and Communications
KW - Software
KW - Artificial Intelligence
SN - 1566-113X
TI - New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity
ER -
TY - JOUR
AB - 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.
AU - Iyiola, Olaniyi S.
AU - Shehu, Yekini
ID - 9315
IS - 2
JF - Results in Mathematics
SN - 14226383
TI - New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications
VL - 76
ER -
TY - JOUR
AB - 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.
AU - Shehu, Yekini
AU - Iyiola, Olaniyi S.
ID - 8077
JF - Applied Numerical Mathematics
SN - 0168-9274
TI - Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence
VL - 157
ER -
TY - JOUR
AB - 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.
AU - Shehu, Yekini
AU - Dong, Qiao-Li
AU - Liu, Lu-Lu
AU - Yao, Jen-Chih
ID - 8196
JF - Optimization and Engineering
SN - 1389-4420
TI - New strong convergence method for the sum of two maximal monotone operators
ER -