Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the variables used in a discrete optimization problem are restricted to be discrete variables—that is, to assume only a discrete set of values, such as the integers.[1]
^Lee, Jon (2004), A First Course in Combinatorial Optimization, Cambridge Texts in Applied Mathematics, vol. 36, Cambridge University Press, p. 1, ISBN 9780521010122.
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Discreteoptimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the...
variables are continuous or discrete: An optimization problem with discrete variables is known as a discreteoptimization, in which an object such as...
It is generally divided into two subfields: discreteoptimization and continuous optimization. Optimization problems arise in all quantitative disciplines...
considers discreteoptimization to consist of integer programming together with combinatorial optimization (which in a turn is composed of optimization problems...
Continuous optimization is a branch of optimization in applied mathematics. As opposed to discreteoptimization, the variables used in the objective function...
hyperparameter optimization methods. Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian...
structures without continuity Discreteoptimization, a branch of optimization in applied mathematics and computer science Discrete probability distribution...
4104-4109 Clerc, M. (2004). Discrete Particle Swarm Optimization, illustrated by the Traveling Salesman Problem, New Optimization Techniques in Engineering...
related to subjects such as finite geometry, combinatorial optimization, digital geometry, discrete differential geometry, geometric graph theory, toric geometry...
mathematics and statistics, a quantitative variable may be continuous or discrete if they are typically obtained by measuring or counting, respectively....
numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. As an example, ant colony optimization is a class...
the performance of the system. Topology optimization is different from shape optimization and sizing optimization in the sense that the design can attain...
for multi-objective optimization and multidisciplinary design optimization. LINDO – (Linear, Interactive, and DiscreteOptimizer) a software package for...
In discreteoptimization, a special ordered set (SOS) is an ordered set of variables used as an additional way to specify integrality conditions in an...
dynamic programming equation associated with discrete-time optimization problems. In continuous-time optimization problems, the analogous equation is a partial...
Robust optimization is a field of mathematical optimization theory that deals with optimization problems in which a certain measure of robustness is sought...
TSP. Discrete Applied Mathematics 117 (2002), 81–86. J. Bang-Jensen, G. Gutin and A. Yeo, When the greedy algorithm fails. DiscreteOptimization 1 (2004)...
Bayesian optimization is a sequential design strategy for global optimization of black-box functions that does not assume any functional forms. It is usually...
Research Institute on DiscreteOptimization and Systems Applications of the Systems Science Panel of NATO and of the DiscreteOptimization Symposium. Elsevier...
gives the probability that a discrete random variable is exactly equal to some value. Sometimes it is also known as the discrete probability density function...
Mathematical logic – Subfield of mathematics Discreteoptimization – Branch of mathematical optimization Set theory – Branch of mathematics that studies...
sub-structure of a given discrete structure, such as a graph, a string, a finite group, and so on. The term combinatorial optimization is typically used when...
Discretize the trajectory optimization problem directly, converting it into a constrained parameter optimization problem, 2) Solve that optimization problem...
of the most intensively studied problems in optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally...
relevant to the field of operations research such as continuous optimization, discreteoptimization, game theory, machine learning, simulation methodology, and...
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