About: Minimum Population Search

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In evolutionary computation, Minimum Population Search (MPS) is a computational method that optimizes a problem by iteratively trying to improve a set of candidate solutions with regard to a given measure of quality. It solves a problem by evolving a small population of candidate solutions by means of relatively simple arithmetical operations.

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rdfs:label	Minimum Population Search (en)
rdfs:comment	In evolutionary computation, Minimum Population Search (MPS) is a computational method that optimizes a problem by iteratively trying to improve a set of candidate solutions with regard to a given measure of quality. It solves a problem by evolving a small population of candidate solutions by means of relatively simple arithmetical operations. (en)
dcterms:subject	Metaheuristics Evolutionary algorithms
Wikipage page ID	54928163 (xsd:integer)
Wikipage revision ID	1031752343 (xsd:integer)
Link from a Wikipage to another Wikipage	Metaheuristic Metaheuristics Continuous function Mathematical optimization Estimation of distribution algorithm Quasi-Newton method Gradient Gradient descent Simulated annealing Particle swarm optimization Differential evolution Evolutionary algorithms Brute-force search Optimization problem Evolutionary computation Evolution strategies
Link from a Wikipage to an external page	https://github.com/alxrcs/MPS
sameAs	Minimum Population Search Minimum Population Search
dbp:wikiPageUsesTemplate	dbt:More_footnotes dbt:Reflist dbt:Major_subfields_of_optimization dbt:Optimization_algorithms
has abstract	In evolutionary computation, Minimum Population Search (MPS) is a computational method that optimizes a problem by iteratively trying to improve a set of candidate solutions with regard to a given measure of quality. It solves a problem by evolving a small population of candidate solutions by means of relatively simple arithmetical operations. MPS is a metaheuristic as it makes few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions. For problems where finding the precise global optimum is less important than finding an acceptable local optimum in a fixed amount of time, using a metaheuristic such as MPS may be preferable to alternatives such as brute-force search or gradient descent. MPS is used for multidimensional real-valued functions but does not use the gradient of the problem being optimized, which means MPS does not require for the optimization problem to be differentiable as is required by classic optimization methods such as gradient descent and quasi-newton methods. MPS can therefore also be used on optimization problems that are not even continuous, are noisy, change over time, etc. (en)
prov:wasDerivedFrom	wikipedia-en:Minimum_Population_Search?oldid=1031752343&ns=0
page length (characters) of wiki page	8676 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Minimum_Population_Search
is foaf:primaryTopic of	wikipedia-en:Minimum_Population_Search

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