In this paper, we consider synchronous stationary and nonstationary multi-splitting Schwarz methods for solving the linear complementarity problems. Moreover, We establish two convergence theorems of the methods by us...
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ISBN:
(纸本)9780769534985
In this paper, we consider synchronous stationary and nonstationary multi-splitting Schwarz methods for solving the linear complementarity problems. Moreover, We establish two convergence theorems of the methods by using the concept of H-compatible splitting.
This paper presents a connection between qualitative matrix theory and linear complementarity problems (LCPs). An LCP is said to be sign-solvable if the set of the sign patterns of the solutions is uniquely determined...
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ISBN:
(纸本)9783540727910
This paper presents a connection between qualitative matrix theory and linear complementarity problems (LCPs). An LCP is said to be sign-solvable if the set of the sign patterns of the solutions is uniquely determined by the sign patterns of the given coefficients. We provide a characterization for sign-solvable LCPs such that the coefficient matrix has nonzero diagonals, which can be tested in polynomial time. This characterization leads to an efficient combinatorial algorithm to find the sign pattern of a solution for these LCPs. The algorithm runs in O(gamma) time, where gamma is the number of the nonzero coefficients.
First-order predictor-corrector methods working in a large neighborhood of the central path are among the most efficient interior point methods. In Peng et al. (SIAM J. Optim. 15(4): 1105-1127, 2005), based on a speci...
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First-order predictor-corrector methods working in a large neighborhood of the central path are among the most efficient interior point methods. In Peng et al. (SIAM J. Optim. 15(4): 1105-1127, 2005), based on a specific proximity function, a wide neighborhood of the central path is defined which matches the standard large neighborhood defined by the infinity norm. In this paper, we extend the predictor-corrector algorithm proposed for linear optimization in Peng et al. (SIAM J. Optim. 15(4): 1105-1127, 2005) to P-*(kappa)-linear complementarity problems. Our algorithm performs two kinds of steps. In corrector steps, we use the specific self-regular proximity function to compute the search directions. The predictor step is the same as the predictor step of standard predictor-corrector method in the interior point method literature. We prove that our predictor-corrector algorithm has an O ((1 + 2 kappa)root n log n log (x(0))(T)s(0)/is an element of) iteration bound, which is the best known iteration complexity for problems of this type.
We study uncertain linear complementarity problems (LCPs), that is, problems in which the LCP vector q or the LCP matrix M may contain uncertain parameters. To this end, we use the concept of Gamma-robust optimization...
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We study uncertain linear complementarity problems (LCPs), that is, problems in which the LCP vector q or the LCP matrix M may contain uncertain parameters. To this end, we use the concept of Gamma-robust optimization applied to the gap function formulation of the LCP. Thus, this work builds upon Krebs and Schmidt (2020). There, we studied Gamma-robustified LCPs for l(1)- and box-uncertainty sets, whereas we now focus on ellipsoidal uncertainty sets. For uncertainty in q or M, we derive conditions for the tractability of the robust counterparts. For these counterparts, we also give conditions for the existence and uniqueness of their solutions. Finally, a case study for the uncertain traffic equilibrium problem is considered, which illustrates the effects of the values of Gamma on the feasibility and quality of the respective robustified solutions.
For the large sparse linear complementarity problems (LCP), by adopting the relaxation and relaxation two-sweep techniques for the modulus-based matrix splitting (MMS) iteration method, we establish a double-relaxatio...
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For the large sparse linear complementarity problems (LCP), by adopting the relaxation and relaxation two-sweep techniques for the modulus-based matrix splitting (MMS) iteration method, we establish a double-relaxation two-sweep modulus-based matrix splitting (DRTMMS) iteration method. This new method contains some known ones developed recently. Some sufficient conditions for guaranteeing the convergence of the DRTMMS method are presented when the system matrices are positive definite matrices and H+-matrices, which generalize some existing results. And the parameter selection strategy of the DRTMMS iteration method is given. Besides, the convergence analyses of the DRTM accelerated overrelaxation (DRTMAOR) method are given. Finally, numerical experiments illustrate that the DRTMMS method is efficient and has better performance than several existing MMS-like methods, and outperforms the projected splitting methods in some cases.(c) 2023 Elsevier B.V. All rights reserved.
complementarityproblems are often used to compute equilibria made up of specifically coordinated solutions of different optimization problems. Specific examples are game-theoretic settings like the bimatrix game or e...
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complementarityproblems are often used to compute equilibria made up of specifically coordinated solutions of different optimization problems. Specific examples are game-theoretic settings like the bimatrix game or energy market models like for electricity or natural gas. While optimization under uncertainties is rather well-developed, the field of equilibrium models represented by complementarityproblems under uncertainty - especially using the concepts of robust optimization - is still in its infancy. In this paper, we extend the theory of strictly robust linear complementarity problems (LCPs) to Gamma-robust settings, where existence of worst-case-hedged equilibria cannot be guaranteed. Thus, we study the minimization of the worst-case gap function of Gamma-robust counterparts of LCPs. For box and-norm uncertainty sets we derive tractable convex counterparts for monotone LCPs and study their feasibility as well as the existence and uniqueness of solutions. To this end, we consider uncertainties in the vector and in the matrix defining the LCP. We additionally study so-called rho-robust solutions, i.e. solutions of relaxed uncertain LCPs. Finally, we illustrate the Gamma-robust concept applied to LCPs in the light of the above mentioned classical examples of bimatrix games and market equilibrium modelling.
We prove that every multiplayer quitting game admits a sunspot epsilon-equilibrium for every epsilon> 0, that is, an e-equilibrium in an extended game in which the players observe a public signal at every stage. We...
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We prove that every multiplayer quitting game admits a sunspot epsilon-equilibrium for every epsilon> 0, that is, an e-equilibrium in an extended game in which the players observe a public signal at every stage. We also prove that, if a certain matrix that is derived from the payoffs in the game is not a Q-matrix in the sense of linear complementarity problems, then the game admits a uniform epsilon-equilibrium for every epsilon > 0.
This paper presents a full multigrid (FMG) technique, which combines a multigrid method, an active set algorithm and a nested iteration technique, to solve a linearcomplementarity problem (LCP) modeling elastic norma...
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This paper presents a full multigrid (FMG) technique, which combines a multigrid method, an active set algorithm and a nested iteration technique, to solve a linearcomplementarity problem (LCP) modeling elastic normal contact problems. The governing system in this LCP is derived from a Fredholm integral of the first kind, and its coefficient matrix is dense, symmetric and positive definite. One multigrid cycle is applied to solve this system approximately in each active set iteration. Moreover, this multigrid solver incorporates a special strategy to handle the complementarity conditions, including restricting both the defect and the contact area (active set) to the coarse grid, and setting all quantities outside contact to zero. The smoother is chosen by some analysis based on the eigenvectors of the iteration matrix. This method is applied to a Hertzian smooth contact and a rough surface contact problem.
linear complementarity problems (LCPs) are an important modeling tool for many practically relevant situations and also have many important applications in mathematics itself. Although the continuous version of the pr...
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linear complementarity problems (LCPs) are an important modeling tool for many practically relevant situations and also have many important applications in mathematics itself. Although the continuous version of the problem is extremely well-studied, much less is known about mixed-integer LCPs (MILCPs) in which some variables have to be integer-valued in a solution. In particular, almost no tailored algorithms are known besides reformulations of the problem that allow us to apply general purpose mixed integer linear programming solvers. In this paper, we present, theoretically analyze, enhance, and test a novel branch-and-bound method for MILCPs. The main property of this method is that we do not "branch" on constraints as usual but by adding suitably chosen penalty terms to the objective function. By doing so, we can either provably compute an MILCP solution if one exists or compute an approximate solution that minimizes an infeasibility measure combining integrality and complementarity conditions. We enhance the method by MILCP-tailored valid inequalities, node selection strategies, branching rules, and warm-starting techniques. The resulting algorithm is shown to clearly outperform two benchmark approaches from the literature.
Many systems of interest to control engineering can be modeled by linear complementarity problems. We introduce a new notion of equivalence between linear complementarity problems that sets the basis to translate the ...
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Many systems of interest to control engineering can be modeled by linear complementarity problems. We introduce a new notion of equivalence between linear complementarity problems that sets the basis to translate the powerful tools of smooth bifurcation theory to this class of models. Leveraging this notion of equivalence, we introduce new tools to analyze, classify, and design nonsmooth bifurcations in linear complementarity problems and their interconnection.
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