We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We show that our bound can outperform both the Lov\'asz theta number and the Haemers minimum rank bound. As a by-produ...
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A risk explicit interval linear programming model for CCHP system optimization was proposed to provide better system cost-risk tradeoff for decision making. This method is an improved interval parameter programming, w...
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In this paper, the alternative duality schemes for mathematical programming problems are considered. These schemes are based on the Lagrange function regularized by Tikhonov in primal and dual variables simultaneously...
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In this paper, a robust linear programming is considered, where all of its coefficients in the objective function and constraints are rough intervals or IT2 rough interval coefficients. First, we allow the IT2 rough i...
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Temporal reasoning problems occur in many application domains of Artificial Intelligence;therefore, it is important for us to develop algorithms for solving them efficiently. While some problems like Simple Temporal P...
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This paper presents a novel approach for solving linear programming Problems in an Intuitionistic Fuzzy environment. Here, the cost coefficients in the objective function of an Intuitionistic Fuzzy Number linear Progr...
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This paper proposes a new partial tracking method, based on linear programming, that can run in real-time, is simple to implement, and performs well in difficult tracking situations by considering spurious peaks, cros...
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linear programming (LP) formulations are often employed to solve stationary, infinite-horizon Markov decision process (MDP) models. We present an LP approach to solving non-stationary, finite-horizon MDP models that c...
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linear programming (LP) formulations are often employed to solve stationary, infinite-horizon Markov decision process (MDP) models. We present an LP approach to solving non-stationary, finite-horizon MDP models that can potentially overcome the computational challenges of standard MDP solution procedures. Specifically, we establish the existence of an LP formulation for risk-neutral MDP models whose states and transition probabilities are temporally heterogeneous. This formulation can be recast as an approximate linear programming formulation with significantly fewer decision variables. (C) 2017 Elsevier B.V. All rights reserved.
This paper focuses on spatial-temporal allocation of the sensors in multi-fighter cooperative detection. Airborne sensor must be coordinated efficiently to detect battlefield situation for finishing the operation whic...
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We study the intersection of finitely generated factor-free subgroups of free products of groups by utilizing the method of linear programming. For example, we prove that if H-1 is a finitely generated factor-free non...
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We study the intersection of finitely generated factor-free subgroups of free products of groups by utilizing the method of linear programming. For example, we prove that if H-1 is a finitely generated factor-free noncyclic subgroup of the free product G(1) * G(2) of two finite groups G(1), G(2), then the WN-coefficient sigma(H-1) of H-1 is rational and can be computed in exponential time in the size of H-1. This coefficient sigma (H-1)is the minimal positive real number such that, for every finitely generated factor-free subgroup H-2 of G(1)* G(2), it is true that (r) over bar (H-1, H-2) <= sigma (H-1) (r) over bar (H-1)(r) over bar (H-2), where (r) over bar (H) = max(r(H) - 1,0) is the reduced rank of H, r (H) is the rank of H, and (r) over bar (H-1, H-2) is the reduced rank of the generalized intersection of H-1 and H-2. In the case of the free product G(1) * G(2) of two finite groups G(1), G(2), it is also proved that there exists a factor-free subgroup H-2* = H-2*= (H-1) such that (r) over bar (H-1, H-2*) = sigma (H-1)(r) over bar (H-1)(r) over bar (H-2 ),H-2* has at most doubly exponential size in the size of H-1, and H-2* can be constructed in exponential time in the size of H-1.
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