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What (who) is classical optimization problem - definition
PROBLEMS INVOLVING THE SELECTION OF AN OPTIMAL ELEMENT FROM SETS OF AVAILABLE ALTERNATIVES
Optimal solution; Optimal value; Multimodal optimization problem
Optimization problem
In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions.
Multi-objective optimization
![Example of a [[Pareto frontier]] (in red), the set of Pareto optimal solutions (those that are not dominated by any other feasible solutions). The boxed points represent feasible choices, and smaller values are preferred to larger ones. Point ''C'' is not on the Pareto frontier because it is dominated by both point ''A'' and point ''B''. Points ''A'' and ''B'' are not strictly dominated by any other, and hence do lie on the frontier.](https://commons.wikimedia.org/wiki/Special:FilePath/Front pareto.svg?width=200 "Example of a [[Pareto frontier]] (in red), the set of Pareto optimal solutions (those that are not dominated by any other feasible solutions). The boxed points represent feasible choices, and smaller values are preferred to larger ones. Point ''C'' is not on the Pareto frontier because it is dominated by both point ''A'' and point ''B''. Points ''A'' and ''B'' are not strictly dominated by any other, and hence do lie on the frontier.")
AREA OF MULTIPLE CRITERIA DECISION MAKING, THAT IS CONCERNED WITH MATHEMATICAL OPTIMIZATION PROBLEMS INVOLVING MORE THAN ONE OBJECTIVE FUNCTION TO BE OPTIMIZED SIMULTANEOUSLY
Multiobjective problem; Multiobjective programming; Multiple objective optimization; Multiobjective optimisation; Multiobjective optimization; NSGA-II; Non-dominated Sorting Genetic Algorithm-II; Solutions of multi-objective optimization problems; Multivariate optimization; Multicriteria optimization; Bicriteria optimization; Pareto optimization
Multi-objective optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization) is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective optimization has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives.
Mathematical optimization
STUDY OF MATHEMATICAL ALGORITHMS FOR OPTIMIZATION PROBLEMS
Mathematical programming; Optimisation; Optimization theory; Cost functional; Optimal; Optimum; Searching the search space; Optimisation (mathematics); Optimization glossary; Numerical optimization; Mathematical optimisation; Optimizer; Optimation; Ordinal optimization; Energy function; Optimizing; Function optimization; Optimization algorithm; Optimal allocation; Optimization; Optimization (mathematics); Numerical optimisation; Optimally; Make the most out of; Make the most of; Numerical optimization problem; Computational optimization techniques; Mathematical optimization algorithms; Applications of mathematical optimization; Applications of optimization; Algorithms for optimization; Algorithms for solving optimization problems; Automated optimization; Interior solution (optimization); History of mathematical optimization; Algorithm's optimality; Optimization problems in economics; Optimization problems in electrical engineering; Optimization of electrical circuits; Optimization of electronic circuits; Optimization heuristic; Optimization (mathematical); Optimization in electrical engineering
Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives."The Nature of Mathematical Programming ," Mathematical Programming Glossary, INFORMS Computing Society.
Wikipedia
Optimization problem
In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions.
Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete:
- An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.
- A problem with continuous variables is known as a continuous optimization, in which an optimal value from a continuous function must be found. They can include constrained problems and multimodal problems.
