Hybrid Newton-type method for a class of semismooth equations

In this paper, we present a hybrid method for the solution of a class of composite semismooth equations encountered frequently in applications. The method is obtained by combining a generalized finite-difference Newton method to an inexpensive direct search method. We prove that, under standard assumptions, the method is globally convergent with a local rate of convergence which is superlinear or quadratic. We report also several numerical results obtained applying the method to suitable reformulations of well-known nonlinear complementarity problem

Direct search methods for influence maximization problems

openThe influence maximization problem seeks to maximize the spread of influence in network structures. This challenging optimization task remains unsolved due to its combinatorial nature and computational complexity. In this thesis, we propose two novel direct search methods, Neighbors Search (NS) and nonmonotone NS, which leverage the network structure to enhance efficiency. We compare these methods with the state-of-the-art Custom Direct Search (CDS) method through experiments on artificial and real-world networks. Our findings show promising improvements in solving the influence maximization problem.The influence maximization problem seeks to maximize the spread of influence in network structures. This challenging optimization task remains unsolved due to its combinatorial nature and computational complexity. In this thesis, we propose two novel direct search methods, Neighbors Search (NS) and nonmonotone NS, which leverage the network structure to enhance efficiency. We compare these methods with the state-of-the-art Custom Direct Search (CDS) method through experiments on artificial and real-world networks. Our findings show promising improvements in solving the influence maximization problem

Direct Search for Dark Matter - Striking the Balance - and the Future

Weakly Interacting Massive Particles (WIMPs) are among the main candidates for the relic dark matter (DM). The idea of the direct DM detection relies on elastic spin-dependent (SD) and spin-independent (SI) interaction of WIMPs with target nuclei. In this review paper the relevant formulae for WIMP event rate calculations are collected. For estimations of the WIMP-proton and WIMP-neutron SD and SI cross sections the effective low-energy minimal supersymmetric standard model is used. The traditional one-coupling-dominance approach for evaluation of the exclusion curves is described. Further, the mixed spin-scalar coupling approach is discussed. It is demonstrated, taking the high-spin Ge-73 dark matter experiment HDMS as an example, how one can drastically improve the sensitivity of the exclusion curves within the mixed spin-scalar coupling approach, as well as due to a new procedure of background subtraction from the measured spectrum. A general discussion on the information obtained from exclusion curves is given. The necessity of clear WIMP direct detection signatures for a solution of the dark matter problem, is pointed out.Comment: LaTeX, 49 pages, 14 figures, 185 reference

Simple Complexity Analysis of Simplified Direct Search

We consider the problem of unconstrained minimization of a smooth function in the derivative-free setting using. In particular, we propose and study a simplified variant of the direct search method (of direction type), which we call simplified direct search (SDS). Unlike standard direct search methods, which depend on a large number of parameters that need to be tuned, SDS depends on a single scalar parameter only. Despite relevant research activity in direct search methods spanning several decades, complexity guarantees---bounds on the number of function evaluations needed to find an approximate solution---were not established until very recently. In this paper we give a surprisingly brief and unified analysis of SDS for nonconvex, convex and strongly convex functions. We match the existing complexity results for direct search in their dependence on the problem dimension ($n$) and error tolerance ($\epsilon$), but the overall bounds are simpler, easier to interpret, and have better dependence on other problem parameters. In particular, we show that for the set of directions formed by the standard coordinate vectors and their negatives, the number of function evaluations needed to find an $\epsilon$-solution is $O(n^2 /\epsilon)$ (resp. $O(n^2 \log(1/\epsilon))$) for the problem of minimizing a convex (resp. strongly convex) smooth function. In the nonconvex smooth case, the bound is $O(n^2/\epsilon^2)$, with the goal being the reduction of the norm of the gradient below $\epsilon$.Comment: 21 pages, 5 algorithms, 1 tabl

Application of Pattern Search Method to Power System Economic Load Dispatch

Direct Search (DS) methods are evolutionary algorithms used to solve constrained optimization problems. DS methods do not require information about the gradient of the objective function while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This study examines the usefulness of a constrained pattern search algorithm to solve well-known power system Economic Load Dispatch problem (ELD) with a valve-point effect. For illustrative purposes, the proposed PS technique has been applied to various test systems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method have been assessed and investigated through comparison with results reported in literature. The outcome is very encouraging and suggests that pattern search (PS) may be very useful in solving power system economic load dispatch problems

Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm

This paper describes a Parallel Space Decomposition (PSD) technique for the Mesh Adaptive Direct Search (MADS) algorithm. MADS extends Generalized Pattern Search for constrained nonsmooth optimization problems. The objective here is to solve larger problems more efficiently. The new method (PSD-MADS) is an asynchronous parallel algorithm in which the processes solve problems over subsets of variables. The convergence analysis based on the Clarke calculus is essentially the same as for the MADS algorithm. A practical implementation is described and some numerical results on problems with up to 500 variables illustrate advantages and limitations of PSD-MADS

Application of pattern search method to power system valve-point economic load dispatch

Direct search (DS) methods are evolutionary algorithms used to solve constrained optimization problems. DS methods do not require any information about the gradient of the objective function at hand, while searching for an optimum solution. One of such methods is pattern search (PS) algorithm. This study presents a new approach based on a constrained pattern search algorithm to solve well-known power system economic load dispatch problem (ELD) with valve-point effect. For illustrative purposes, the proposed PS technique has been applied to various test systems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method has been assessed and investigated through comparison with results reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving power system economic load dispatch problem

Solution of Different Types of Economic Load Dispatch Problems Using a Pattern Search Method

Direct search (DS) methods are evolutionary algorithms used to solve constrained optimization problems. DS methods do not require information about the gradient of the objective function when searching for an optimum solution. One such method is a pattern search (PS) algorithm. This study presents a new approach based on a constrained PS algorithm to solve various types of power system economic load dispatch (ELD) problems. These problems include economic dispatch with valve point (EDVP) effects, multi-area economic load dispatch (MAED), companied economic-environmental dispatch (CEED), and cubic cost function economic dispatch (QCFED). For illustrative purposes, the proposed PS technique has been applied to each of the above dispatch problems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method has been assessed and investigated through comparison with results reported in literature. The outcome is very encouraging and suggests that PS methods may be very efficient when solving power system ELD problems