Optimization Task
(Redirected from Numerical Optimization)
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An Optimization Task is a search task for an optimal solution from within a search space based on a utility function.
- AKA: Cost Function Optimization, Numerical Optimization.
- Context:
- Input: Search Space, and a Cost Function.
- output: Optimal Solution.
- It can range from being a Minimization Task to being a Maximization Task.
- It can range from being a Combinatorial Optimization Task to being a Continuous Optimization Task.
- It can range from being an Exact Optimization Task to being an Approximate Optimization Task.
- It can range from being an Unconstrained Optimization Task to being a Constrained Optimization Task.
- It can be solved by an Optimization System (that implements an optimization algorithm).
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- Example(s):
- Counter-Example(s):
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- See: Constraint Satisfaction, Function Selection Task, Optimization Task Decomposition.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/optimization_problem Retrieved:2015-6-13.
- In mathematics and computer science, 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 combinatorial optimization problem. In a combinatorial optimization problem, we are looking for an object such as an integer, permutation or graph from a finite (or possibly countable infinite) set.