Genetic Algorithms as Optimalisation Procedures
Drawing a parallel between biological and economic evolution provides an opportunity for the description of dynamic economic processes changing in time by using genetic algorithms. The first step in finding algorithms in biological and economic processes is to draw a parallel between the terms used...
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| Format: | Article |
| Language: | English |
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University of Miskolc
2007-02-01
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| Series: | Theory, Methodology, Practice |
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| Online Access: | https://ojs.uni-miskolc.hu/index.php/tmp/article/view/1335 |
| _version_ | 1827782339447488512 |
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| author | Sándor Karajz |
| author_facet | Sándor Karajz |
| author_sort | Sándor Karajz |
| collection | DOAJ |
| description |
Drawing a parallel between biological and economic evolution provides an opportunity for the description of dynamic economic
processes changing in time by using genetic algorithms. The first step in finding algorithms in biological and economic processes is
to draw a parallel between the terms used in both disciplines and to determine the degree of elaboration of analogues. On the basis
of these ideas it can be stated that most biological terms can be used both in economics and in the social field, which satisfies the
essential condition for successful modeling.
Genetic algorithms are derived on the basis of Darwin-type biological evolution and the process starts from a possible state
(population), in most cases chosen at random. New generations emerge from this starting generation on the basis of various
procedures. These generating procedures go on until the best solution to the problem is found. Selection, recombination and
mutation are the most important genetic procedures.
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| first_indexed | 2024-03-11T15:30:49Z |
| format | Article |
| id | doaj.art-20f3b6de61554675acca577c1bc1096d |
| institution | Directory Open Access Journal |
| issn | 1589-3413 2415-9883 |
| language | English |
| last_indexed | 2024-03-11T15:30:49Z |
| publishDate | 2007-02-01 |
| publisher | University of Miskolc |
| record_format | Article |
| series | Theory, Methodology, Practice |
| spelling | doaj.art-20f3b6de61554675acca577c1bc1096d2023-10-27T04:14:01ZengUniversity of MiskolcTheory, Methodology, Practice1589-34132415-98832007-02-01401Genetic Algorithms as Optimalisation ProceduresSándor Karajz0University of Miskolc Drawing a parallel between biological and economic evolution provides an opportunity for the description of dynamic economic processes changing in time by using genetic algorithms. The first step in finding algorithms in biological and economic processes is to draw a parallel between the terms used in both disciplines and to determine the degree of elaboration of analogues. On the basis of these ideas it can be stated that most biological terms can be used both in economics and in the social field, which satisfies the essential condition for successful modeling. Genetic algorithms are derived on the basis of Darwin-type biological evolution and the process starts from a possible state (population), in most cases chosen at random. New generations emerge from this starting generation on the basis of various procedures. These generating procedures go on until the best solution to the problem is found. Selection, recombination and mutation are the most important genetic procedures. https://ojs.uni-miskolc.hu/index.php/tmp/article/view/1335Genetic AlgorithmsOptimalisation Procedures |
| spellingShingle | Sándor Karajz Genetic Algorithms as Optimalisation Procedures Theory, Methodology, Practice Genetic Algorithms Optimalisation Procedures |
| title | Genetic Algorithms as Optimalisation Procedures |
| title_full | Genetic Algorithms as Optimalisation Procedures |
| title_fullStr | Genetic Algorithms as Optimalisation Procedures |
| title_full_unstemmed | Genetic Algorithms as Optimalisation Procedures |
| title_short | Genetic Algorithms as Optimalisation Procedures |
| title_sort | genetic algorithms as optimalisation procedures |
| topic | Genetic Algorithms Optimalisation Procedures |
| url | https://ojs.uni-miskolc.hu/index.php/tmp/article/view/1335 |
| work_keys_str_mv | AT sandorkarajz geneticalgorithmsasoptimalisationprocedures |