Results 261 to 270 of about 904,011 (327)
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2000
In this chapter, we introduce a class of methods that were among the first to be designed for the solution of integer programming problems. Throughout the past decades, however, computational evidence has revealed that cutting planes, while appealing from a theoretical point of view, do not appear to work very well if applied to general integer ...
H. A. Eiselt, C.-L. Sandblom
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In this chapter, we introduce a class of methods that were among the first to be designed for the solution of integer programming problems. Throughout the past decades, however, computational evidence has revealed that cutting planes, while appealing from a theoretical point of view, do not appear to work very well if applied to general integer ...
H. A. Eiselt, C.-L. Sandblom
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2014
Subgradient methods described in the previous chapter use only one arbitrary subgradient (generalized gradient) at a time, without memory of past iterations. If the information from previous iterations is kept, it is possible to define a model—the so-called cutting plane model—of the objective function.
Adil Bagirov +2 more
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Subgradient methods described in the previous chapter use only one arbitrary subgradient (generalized gradient) at a time, without memory of past iterations. If the information from previous iterations is kept, it is possible to define a model—the so-called cutting plane model—of the objective function.
Adil Bagirov +2 more
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Probabilistic analytic center cutting plane method with multiple cuts
2014 European Control Conference (ECC), 2014A probabilistic analytic center cutting plane method with multiple cuts is proposed for a class of robust feasibility problems which is to find a solution satisfying a set of parameter dependent convex constraints for all possible parameter values. In particular, a new update rule is presented for constructing a smaller polytope which contains the ...
Takayuki Wada, Yasumasa Fujisaki
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Cutting-Plane Methods without Nested Constraint Sets
Operations Research, 1970This paper gives general conditions for the convergence of a class of cutting-plane algorithms without requiring that the constraint sets for the sub-problems be sequentially nested. Conditions are given under which inactive constraints may be dropped after each subproblem.
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Polynomial Interior Point Cutting Plane Methods
Optimization Methods and Software, 2003Polynomial cutting plane methods based on the logarithmic barrier function and on the volumetric center are surveyed. These algorithms construct a linear programing relaxation of the feasible region, find an appropriate approximate center of the region, and call a separation oracle at this approximate center to determine whether additional constraints ...
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Cutting-Plane Theory: Disjunctive Methods
1977This paper is a survey, with new results, of the disjunctive methods of cutting-plane theory, which were devised by Balas, Glover, Owen, Young, and other researchers, over the past half decade. The basic disjunctive cut principle is derived, its interrelations with the other cut-producing procedures are discussed, and applications of it are given. Many
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Interior Proximal Method Without the Cutting Plane Property
Journal of Optimization Theory and Applications, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Cutting method for finding discrete minimax with dropping of cutting planes
Lobachevskii Journal of Mathematics, 2014Cutting algorithms with partial embedding of the admissible set and with periodical dropping of planes are commonly used in solving conditional minimization problems. The authors extend the implementation to cutting methods that do not approximate the feasible set, but the epigraph of the objective function. The proposed method provides the possibility
Zabotin I., Yarullin R.
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A Cutting Plane Method for Solving Quasimonotone Variational Inequalities
Computational Optimization and Applications, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marcotte, P., Zhu, D. L.
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Accelerating the Cutting Plane Method for Nonlinear Programming
Journal of the Society for Industrial and Applied Mathematics, 1961The “cutting plane” method of Kelley for nonlinear programming problems applies linear programming, through a sequence of local linearizations, to the problem of minimizing a convex function of real variables subject to linear inequality constraints.
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