Examples of 'combinatorial optimization problems' in a sentence
Meaning of "combinatorial optimization problems"
combinatorial optimization problems: This phrase refers to mathematical problems that involve finding the best solution from a finite set of possibilities. It is commonly used in the field of mathematics and computer science
How to use "combinatorial optimization problems" in a sentence
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combinatorial optimization problems
Combinatorial optimization problems are widely studied in the literature.
Association is expressed as combinatorial optimization problems.
Combinatorial optimization problems and their approximability properties.
This type of problem belongs to the combinatorial optimization problems.
See also combinatorial optimization problems.
Simulated annealing is a method used to solve combinatorial optimization problems.
Combinatorial optimization problems such as parsing and the knapsack problem.
We construct a generic procedure in the general context of combinatorial optimization problems.
Combinatorial optimization problems with a stochastic component are a source of challenging open questions.
Routing problems are among the most difficult combinatorial optimization problems.
Modelling and solving combinatorial optimization problems with Branch-and-Cut algorithms.
This problem occurs in particular as a subproblem of many combinatorial optimization problems.
High-speed calculation of combinatorial optimization problems on world 's largest scale.
The task allocation problem is included in this class of combinatorial optimization problems.
NP-hard combinatorial optimization problems are commonly encountered in numerous different domains.
See also
Graphs and Networks Optimization in graphs Paths and cycles Network flows Selected combinatorial optimization problems.
Abstract, Combinatorial optimization problems lie at the core of the theory of algorithmic complexity.
All three problems are NP-hard combinatorial optimization problems.
Abstract, Many Combinatorial Optimization problems consider several, often conflicting, objectives.
Many practical real-life applications can be formulated as combinatorial optimization problems.
Simulated annealing ' algorithms are currently used to solve a wide range of combinatorial optimization problems.
It has been used for solving continuous optimization, integer programming, and combinatorial optimization problems.
In this thesis, we have proposed hybrid metaheuristic algorithms for solving multi-objective combinatorial optimization problems.
Abstract, Scheduling problems represent an important class of combinatorial optimization problems.
Abstract, Many practical situations can be modeled as combinatorial optimization problems.
Randomized Search heuristics are frequently applied to NP-hard combinatorial optimization problems.
Title, Extension of a hybrid-genetic optimization environment by modules for solving combinatorial optimization problems.
Part II deals with local-search techniques applied to geometric restrictions of classical combinatorial optimization problems.
Abstract, The Routing Problem is one of the most popular and challenging combinatorial optimization problems.
Abstract, In this work, we are interested in solving multi-objective combinatorial optimization problems.
Abstract, We elaborate a multi-agent based optimization method for combinatorial optimization problems named MAOM-COP.
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