integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers...
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be integers, then the problem is called an integer programming (IP) or integer linear programming (ILP) problem. In contrast to linear programming, which...
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linear constraints on the variables. Quadratic programming is a type of nonlinear programming. "Programming" in this context refers to a formal procedure...
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programming relaxation has a value differing from that of the unrelaxed 0–1 integer program. The linear programming relaxation of an integer program may...
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GNU Linear Programming Kit (GLPK) is a software package intended for solving large-scale linear programming (LP), mixed integer programming (MIP), and...
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cuts. Such procedures are commonly used to find integer solutions to mixed integer linear programming (MILP) problems, as well as to solve general, not...
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optimizer) a software package for linear programming, integer programming, nonlinear programming, stochastic programming, and global optimization. The "What's...
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In computer programming, an integer overflow occurs when an arithmetic operation on integers attempts to create a numeric value that is outside of the...
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formulated as a quadratically constrained quadratic program. Since 0–1 integer programming is NP-hard in general, QCQP is also NP-hard. However, even for a...
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AMPL (redirect from AMPL (programming language))
among them: Linear programming Quadratic programming Nonlinear programming Mixed-integer programming Mixed-integer quadratic programming with or without...
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that deals with problems that are not linear. Let n, m, and p be positive integers. Let X be a subset of Rn (usually a box-constrained one), let f, gi, and...
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Graver basis (category Linear programming)
bases enable iterative solutions of linear and various nonlinear integer programming problems in polynomial time. They were introduced by Jack E. Graver...
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Feasible region (section Linear programming)
non-negative. In pure integer programming problems, the feasible set is the set of integers (or some subset thereof). In linear programming problems, the feasible...
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Semidefinite programming (SDP) is a subfield of mathematical programming concerned with the optimization of a linear objective function (a user-specified...
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problems on graphs, matroids and other discrete structures integer programming constraint programming These branches are all closely intertwined however, since...
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for writing integer literals in many programming languages: Many programming languages, especially those influenced by C, prefix an integer literal with...
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Cramer's rule (section Integer programming)
prove that an integer programming problem whose constraint matrix is totally unimodular and whose right-hand side is integer, has integer basic solutions...
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An integer is the number zero (0), a positive natural number (1, 2, 3, . . .), or the negation of a positive natural number (−1, −2, −3, . . .). The negations...
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Dynamic Programming in Macroeconomic Models." An introduction to dynamic programming as an important tool in economic theory. Dynamic Programming: from...
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Data type (redirect from Type (computer programming))
the programmer intends to use the data. Most programming languages support basic data types of integer numbers (of varying sizes), floating-point numbers...
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closely connected to the theory of linear programming and integer programming. Both linear programs and integer programs are expressed in canonical form as seeking...
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PA is in P, and this extends to fixed-dimensional parametric integer linear programming. Because Presburger arithmetic is decidable, automatic theorem...
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This approach is used for a number of NP-hard problems: Integer programming Nonlinear programming Travelling salesman problem (TSP) Quadratic assignment...
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Simplex algorithm (category Linear programming)
"Simplex algorithms". In J. E. Beasley (ed.). Advances in linear and integer programming. Oxford Science. pp. 1–46. MR 1438309. Maros, István (2003). Computational...
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integers Chance constrained programming for dealing with constraints that must be satisfied with a given probability Stochastic dynamic programming Markov...
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diverse range of SQP methods. Sequential linear programming Sequential linear-quadratic programming Augmented Lagrangian method SQP methods have been...
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combinatorial optimization for solving integer linear programming (ILP) and mixed integer linear programming (MILP) problems with many variables. The...
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satisfaction problem Cutting stock problem Dominating set problem Integer programming Job shop scheduling Knapsack problem Minimum relevant variables in...
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multiparametric programming problem If integer variables are present, then the problem is referred to as (multi)parametric mixed-integer programming problem If...
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by IBM. The IBM ILOG CPLEX Optimizer solves integer programming problems, very large linear programming problems using either primal or dual variants...
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