Evolutionary programming

Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover.^[1]^[2] Evolutionary programming differs from evolution strategy ES( $\mu +\lambda$ ) only in one detail.^[1] All individuals are selected for the new population, while in ES( $\mu +\lambda$ ), every individual has the same probability to be selected. It is one of the four major evolutionary algorithm paradigms.^[3]

History

It was first used by Lawrence J. Fogel in the US in 1960 in order to use simulated evolution as a learning process aiming to generate artificial intelligence.^[4] It was used to evolve finite-state machines as predictors.^[5]

Timeline of EP - selected algorithms^[1]
Year	Description	Reference
1966	EP introduced by Fogel et al.	^[6]
1992	Improved fast EP - Cauchy mutation is used instead of Gaussian mutation	^[7]
2002	Generalized EP - usage of Lévy-type mutation	^[8]
2012	Diversity-guided EP - Mutation step size is guided by diversity	^[9]
2013	Adaptive EP - The number of successful mutations determines the strategy parameter	^[10]
2014	Social EP - Social cognitive model is applied meaning replacing individuals with cognitive agents	^[11]
2015	Immunised EP - Artificial immune system inspired mutation and selection	^[12]
2016	Mixed mutation strategy EP - Gaussian, Cauchy and Levy mutations are used	^[13]
2017	Fast Convergence EP - An algorithm, which boosts convergence speed and solution quality	^[14]
2017	Immune log-normal EP - log-normal mutation combined with artificial immune system	^[15]
2018	ADM-EP - automatically designed mutation operators	^[16]

References

^ ^a ^b ^c Slowik, Adam; Kwasnicka, Halina (1 August 2020). "Evolutionary algorithms and their applications to engineering problems". Neural Computing and Applications. 32 (16): 12363–12379. doi:10.1007/s00521-020-04832-8. ISSN 1433-3058.
^ Abido, Mohammad A.; Elazouni, Ashraf (30 November 2021). "Modified multi-objective evolutionary programming algorithm for solving project scheduling problems". Expert Systems with Applications. 183: 115338. doi:10.1016/j.eswa.2021.115338. ISSN 0957-4174.
^ Brameier, Markus (2004). "On Linear Genetic Programming". Dissertation. Retrieved 27 December 2024.
^ "Artificial Intelligence through Simulated Evolution". Evolutionary Computation. 2009. doi:10.1109/9780470544600.ch7.
^ Abraham, Ajith; Nedjah, Nadia; Mourelle, Luiza de Macedo (2006). "Evolutionary Computation: from Genetic Algorithms to Genetic Programming". Genetic Systems Programming: Theory and Experiences. Springer: 1–20. doi:10.1007/3-540-32498-4_1.
^ Fogel, LJ; Owens, AJ; Walsh, MJ (1966). rtificial intelligence thorough simulated evolution. New York: Wiley.
^ "Evolutionary programming made faster". IEEE Transactions on Evolutionary Computation. 3 (2): 82–102. July 1999. doi:10.1109/4235.771163.
^ Iwamatsu, Masao (1 August 2002). "Generalized evolutionary programming with Lévy-type mutation". Computer Physics Communications. 147 (1): 729–732. doi:10.1016/S0010-4655(02)00386-7. ISSN 0010-4655.
^ Alam, Mohammad Shafiul; Islam, Md. Monirul; Yao, Xin; Murase, Kazuyuki (1 June 2012). "Diversity Guided Evolutionary Programming: A novel approach for continuous optimization". Applied Soft Computing. 12 (6): 1693–1707. doi:10.1016/j.asoc.2012.02.002. ISSN 1568-4946.
^ Das, Swagatam; Mallipeddi, Rammohan; Maity, Dipankar (1 April 2013). "Adaptive evolutionary programming with p-best mutation strategy". Swarm and Evolutionary Computation. 9: 58–68. doi:10.1016/j.swevo.2012.11.002. ISSN 2210-6502.
^ Nan, LI; Xiaomin, BAI; Shouzhen, ZHU; Jinghong, ZHENG (1 January 2014). "Social Evolutionary Programming Algorithm onUnit Commitment in Wind Power Integrated System". IFAC Proceedings Volumes. 47 (3): 3611–3616. doi:10.3182/20140824-6-ZA-1003.00384. ISSN 1474-6670.
^ Gao, Wei (1 August 2015). "Slope stability analysis based on immunised evolutionary programming". Environmental Earth Sciences. 74 (4): 3357–3369. doi:10.1007/s12665-015-4372-0. ISSN 1866-6299.
^ Pang, Jinwei; Dong, Hongbin; He, Jun; Feng, Qi (July 2016). "Mixed mutation strategy evolutionary programming based on Shapley value". 2016 IEEE Congress on Evolutionary Computation (CEC): 2805–2812. doi:10.1109/CEC.2016.7744143.
^ Basu, Mousumi (14 September 2017). "Fast Convergence Evolutionary Programming for Multi-area Economic Dispatch". Electric Power Components and Systems. 45 (15): 1629–1637. doi:10.1080/15325008.2017.1376234. ISSN 1532-5008.
^ Mansor, M.H.; Musirin, I.; Othman, M.M. (April 2017). "Immune Log-Normal Evolutionary Programming (ILNEP) for solving economic dispatch problem with prohibited operating zones". 2017 4th International Conference on Industrial Engineering and Applications (ICIEA): 163–167. doi:10.1109/IEA.2017.7939199.
^ Hong, Libin; Drake, John H.; Woodward, John R.; Özcan, Ender (1 January 2018). "A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming". Applied Soft Computing. 62: 162–175. doi:10.1016/j.asoc.2017.10.002. ISSN 1568-4946.

External links

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[overview-1] Slowik, Adam; Kwasnicka, Halina (1 August 2020). "Evolutionary algorithms and their applications to engineering problems". Neural Computing and Applications. 32 (16): 12363–12379. doi:10.1007/s00521-020-04832-8. ISSN 1433-3058.

[2] Abido, Mohammad A.; Elazouni, Ashraf (30 November 2021). "Modified multi-objective evolutionary programming algorithm for solving project scheduling problems". Expert Systems with Applications. 183: 115338. doi:10.1016/j.eswa.2021.115338. ISSN 0957-4174.

[3] Brameier, Markus (2004). "On Linear Genetic Programming". Dissertation. Retrieved 27 December 2024.

[4] "Artificial Intelligence through Simulated Evolution". Evolutionary Computation. 2009. doi:10.1109/9780470544600.ch7.

[5] Abraham, Ajith; Nedjah, Nadia; Mourelle, Luiza de Macedo (2006). "Evolutionary Computation: from Genetic Algorithms to Genetic Programming". Genetic Systems Programming: Theory and Experiences. Springer: 1–20. doi:10.1007/3-540-32498-4_1.

[6] Fogel, LJ; Owens, AJ; Walsh, MJ (1966). rtificial intelligence thorough simulated evolution. New York: Wiley.

[7] "Evolutionary programming made faster". IEEE Transactions on Evolutionary Computation. 3 (2): 82–102. July 1999. doi:10.1109/4235.771163.

[8] Iwamatsu, Masao (1 August 2002). "Generalized evolutionary programming with Lévy-type mutation". Computer Physics Communications. 147 (1): 729–732. doi:10.1016/S0010-4655(02)00386-7. ISSN 0010-4655.

[9] Alam, Mohammad Shafiul; Islam, Md. Monirul; Yao, Xin; Murase, Kazuyuki (1 June 2012). "Diversity Guided Evolutionary Programming: A novel approach for continuous optimization". Applied Soft Computing. 12 (6): 1693–1707. doi:10.1016/j.asoc.2012.02.002. ISSN 1568-4946.

[10] Das, Swagatam; Mallipeddi, Rammohan; Maity, Dipankar (1 April 2013). "Adaptive evolutionary programming with p-best mutation strategy". Swarm and Evolutionary Computation. 9: 58–68. doi:10.1016/j.swevo.2012.11.002. ISSN 2210-6502.

[11] Nan, LI; Xiaomin, BAI; Shouzhen, ZHU; Jinghong, ZHENG (1 January 2014). "Social Evolutionary Programming Algorithm onUnit Commitment in Wind Power Integrated System". IFAC Proceedings Volumes. 47 (3): 3611–3616. doi:10.3182/20140824-6-ZA-1003.00384. ISSN 1474-6670.

[12] Gao, Wei (1 August 2015). "Slope stability analysis based on immunised evolutionary programming". Environmental Earth Sciences. 74 (4): 3357–3369. doi:10.1007/s12665-015-4372-0. ISSN 1866-6299.

[13] Pang, Jinwei; Dong, Hongbin; He, Jun; Feng, Qi (July 2016). "Mixed mutation strategy evolutionary programming based on Shapley value". 2016 IEEE Congress on Evolutionary Computation (CEC): 2805–2812. doi:10.1109/CEC.2016.7744143.

[14] Basu, Mousumi (14 September 2017). "Fast Convergence Evolutionary Programming for Multi-area Economic Dispatch". Electric Power Components and Systems. 45 (15): 1629–1637. doi:10.1080/15325008.2017.1376234. ISSN 1532-5008.

[15] Mansor, M.H.; Musirin, I.; Othman, M.M. (April 2017). "Immune Log-Normal Evolutionary Programming (ILNEP) for solving economic dispatch problem with prohibited operating zones". 2017 4th International Conference on Industrial Engineering and Applications (ICIEA): 163–167. doi:10.1109/IEA.2017.7939199.

[16] Hong, Libin; Drake, John H.; Woodward, John R.; Özcan, Ender (1 January 2018). "A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming". Applied Soft Computing. 62: 162–175. doi:10.1016/j.asoc.2017.10.002. ISSN 1568-4946.

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v t e Evolutionary computation
Main Topics	Evolutionary algorithm Evolutionary data mining Evolutionary multimodal optimization Human-based evolutionary computation Interactive evolutionary computation
Algorithms	Cellular evolutionary algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) Cultural algorithm Differential evolution Evolutionary programming Genetic algorithm Genetic programming Gene expression programming Evolution strategy Natural evolution strategy Neuroevolution Learning classifier system
Related techniques	Swarm intelligence Ant colony optimization Bees algorithm Cuckoo search Particle swarm optimization Bacterial Colony Optimization
Metaheuristic methods	Firefly algorithm Harmony search Gaussian adaptation Memetic algorithm
Related topics	Artificial development Artificial intelligence Artificial life Digital organism Evolutionary robotics Fitness function Fitness landscape Fitness approximation Genetic operators Interactive evolutionary computation No free lunch in search and optimization Machine learning Mating pool Premature convergence Program synthesis
Journals	Evolutionary Computation (journal)

History

See also

References

External links