Imperialist competitive algorithm: Difference between revisions

Browse history interactively ← Previous edit Next edit →Content deleted Content addedVisual WikitextInline

Revision as of 10:42, 25 July 2016 editPigrenok (talk \| contribs)1 editm Removed the proposal for deletion because I believe, that the Imperialist Competitive Algorithm is an important type of metaheuristic methods of optimisation and removal of it will make Misplaced Pages a worse data source.← Previous edit		Revision as of 15:22, 25 July 2016 edit undoRuud Koot (talk \| contribs)31,416 edits →Applications: WP:REFSPAM Next edit →
Line 36:		Line 36:
	== Some new points on Meta-heuristic Algorithm ==		== Some new points on Meta-heuristic Algorithm ==
	In January 2016, by calling “Imperialist Competitive Algorithm” a worldwide algorithm, Sepehr Ghaderi, B.Sc. in Industrial Engineering from Iran, changed it into an independent subject. He added two new branches to this type of algorithm called: “speech coding” and “acceptance of failure”. He studied this type of meta-heuristic algorithm in an article titled “Masonic Worldview Based on Three Historical Periods” from a different point of view. By studying the basic patterns written and used by American-Jewish governor-scientists before and after World War II, he analyzed some samples of International political policies in three historical periods.		In January 2016, by calling “Imperialist Competitive Algorithm” a worldwide algorithm, Sepehr Ghaderi, B.Sc. in Industrial Engineering from Iran, changed it into an independent subject. He added two new branches to this type of algorithm called: “speech coding” and “acceptance of failure”. He studied this type of meta-heuristic algorithm in an article titled “Masonic Worldview Based on Three Historical Periods” from a different point of view. By studying the basic patterns written and used by American-Jewish governor-scientists before and after World War II, he analyzed some samples of International political policies in three historical periods.

	== Applications ==
	ICA is used to solve different optimization problems in various areas of engineering and science. The following are some of the applications of this algorithm.
	* Designing controller for industrial systems<ref name=ica_en_2008_en_conf_rajabioun_decentralized_pid_controller_design_mimo_evaporator /><ref name=ica_en_2008_jnl_atashpaz_ijicc_pid_mimo_distillation_column_process /><ref name=ica_en_2007_cnf_atashpaz_optimal_pid_controller_isfs2007 /><ref name=ica_en_2008_en_bchtr_rajabioun_nash_equilibrium_point_achievement /><ref name=ica_en_2009_jnl_atashpaz_decentralized_pid_controller_optimal_shrinkage_gershgorin_bands />
	* Designing Intelligent Recommender Systems<ref name=ica_en_2008_cnf_sepehrirad_recommender_systems />
	* Fuzzy ICA<ref name=Fuzzy_ICA_2014_NC />
	* Fuzzy Controller Design<ref name=Fuzzy_and_Intelligent_Systems_2008/>
	* Solving optimization problems in communication systems.<ref name=ica_en_2009_jnl_khabbazi_minimum_bit_error_rate_beamforming /><ref name=ica_2010_en_jnl_Alikhani_Evaluation_of_Image_Segmentation_Methods /><ref name=ica_2010_en_cnf_Sayadnavard_Wireless_sensor_network_localization />
	* Solving scheduling and production management problems<ref name=ica_en_2010_jnl_nazari_integrated_product_mix_outsourcing /><ref name=ica_en_2009_jnl_jolai_pareto_simulated_annealing_offline_scheduling_problem_with_rejection /><ref name=ica_en_2010_jnl_shokrollahpour_bi_criteria_flowshop /><ref name=ica_2010_en_jnl_Forouharfard_schedule_cross_docking_systems /><ref name=ica_2010_en_jnl_Karimi_scheduling_flexible_flow_shops_ica_electromagnetic /><ref name=ica_2010_en_jnl_Bagher_Balancing_of_stochastic_U_Type_assembly_lines /><ref name=ica_2010_en_jnl_Sarayloo_ica_Dynamic_Cell_Formation /><ref>{{cite journal\|last1=Piroozfard\|first1=H.\|last2=Wong\|first2=K. Y.\|title=An imperialist competitive algorithm for the job shop scheduling problems\|journal=IEEE Industrial Engineering and Engineering Management (IEEM)\|pages=69–73\|doi=10.1109/IEEM.2014.7058602\|year=2014\|isbn=978-1-4799-6410-9}}</ref>
	* Training and analysis of Artificial Neural Networks<ref name=ica_en_2008_jnl_oskouyi_material_properties_characterization_sharp_indentation_test /><ref name=ica_en_2009_cnf_mahmoudi_ann_weights_optimization />
	* Nash Equilibrium Point Achievement<ref name=ica_en_2008_en_bchtr_rajabioun_nash_equilibrium_point_achievement />
	* Design and thermodynamic optimization of plate-fin heat exchangers<ref name=ica_moslem_2011 />
	* Feature selection<ref>Seyed Jalaleddin Mousavi Rad, Fardin Akhlaghian Tab, Kaveh Mollazade, “ Application of Imperialist Competition Algorithm for Feature Selection: A Case Study On Rice Classification”, International Journal of Computer Application, Vol. 40, No.16, 2012</ref><ref>S.J. Mousavirad, H. Ebrahimpour, Feature selection using modified Imperilaist Competitive Algorithm, International Conference on Computer and Knowledge Engineering(ICKKE 2013), October 31 & November 1, 2013, Ferdowsi University of Mashhad, Mashhad, Iran</ref>
	* and so on<ref name=ica_en_2010_jnl_lucas_linear_induction_motor /><ref name=ica_2010_en_jnl_omid_phev /><ref name=ica_2010_en_jnl_niknam_k_means_clustering /><ref name=ica_2010_en_jnl_mozafari_thin_interphase />

	== References ==		== References ==

Revision as of 15:22, 25 July 2016

This article is an orphan, as no other articles link to it. Please introduce links to this page from related articles; try the Find link tool for suggestions. (April 2016)

In computer science, Imperialist Competitive Algorithm (ICA) is a computational method that is used to solve optimization problems of different types. Like most of the methods in the area of evolutionary computation, ICA does not need the gradient of the function in its optimization process.

From a specific point of view, ICA can be thought of as the social counterpart of genetic algorithms (GAs). ICA is the mathematical model and the computer simulation of human social evolution, while GAs are based on the biological evolution of species.

Applications, advantages and disadvantages of ICA are discussed with details in

Algorithm

Figure 1 shows the flowchart of the Imperialist Competitive Algorithm. This algorithm starts by generating a set of candidate random solutions in the search space of the optimization problem. The generated random points are called the initial Countries. Countries in this algorithm are the counterpart of Chromosomes in GAs and Particles in Particle Swarm Optimization (PSO) and it is an array of values of a candidate solution of optimization problem. The cost function of the optimization problem determines the power of each country. Based on their power, some of the best initial countries (the countries with the least cost function value), become Imperialists and start taking control of other countries (called colonies) and form the initial Empires.

Two main operators of this algorithm are Assimilation and Revolution. Assimilation makes the colonies of each empire get closer to the imperialist state in the space of socio-political characteristics (optimization search space). Revolution brings about sudden random changes in the position of some of the countries in the search space. During assimilation and revolution a colony might reach a better position and has the chance to take the control of the entire empire and replace the current imperialist state of the empire.

Imperialistic Competition is another part of this algorithm. All the empires try to win this game and take possession of colonies of other empires. In each step of the algorithm, based on their power, all the empires have a chance to take control of one or more of the colonies of the weakest empire.

Algorithm continues with the mentioned steps (Assimilation, Revolution, Competition) until a stop condition is satisfied.

Pseudocode

The above steps can be summarized as the below pseudocode.

0) Define objective function:  $f(\mathbf {x} ),\quad \mathbf {x} =(x_{1},x_{2},\dots ,x_{d});\,$ 
1) Initialization of the algorithm. Generate some random solution in the search space and create initial empires.
    2) Assimilation: Colonies move towards imperialist states in different in directions.
    3) Revolution: Random changes occur in the characteristics of some countries.
    4) Position exchange between a colony and Imperialist. A colony with a better position than the imperialist,
       has the chance to take the control of empire by replacing the existing imperialist.
    5) Imperialistic competition: All imperialists compete to take possession of colonies of each other.
    6) Eliminate the powerless empires. Weak empires lose their power gradually and they will finally be eliminated.
    7) If the stop condition is satisfied, stop, if not go to 2.
8) End

Variants

Like for PSO, the first version of ICA was proposed for solving continuous optimization problems. Then in other works different variants of ICA were proposed for solving both discrete and continuous problems. For example Chaotic ICA is proposed by Duan, etal. and also a version of this algorithm for handling constrained optimization problems is proposed by Zhang, etal.

Some new points on Meta-heuristic Algorithm

In January 2016, by calling “Imperialist Competitive Algorithm” a worldwide algorithm, Sepehr Ghaderi, B.Sc. in Industrial Engineering from Iran, changed it into an independent subject. He added two new branches to this type of algorithm called: “speech coding” and “acceptance of failure”. He studied this type of meta-heuristic algorithm in an article titled “Masonic Worldview Based on Three Historical Periods” from a different point of view. By studying the basic patterns written and used by American-Jewish governor-scientists before and after World War II, he analyzed some samples of International political policies in three historical periods.

References

^ Atashpaz-Gargari, E.; Lucas, C (2007). "Imperialist Competitive Algorithm: An algorithm for optimization inspired by imperialistic competition". IEEE Congress on Evolutionary Computation. Vol. 7. pp. 4661–4666. {{cite conference}}: Unknown parameter |booktitle= ignored (|book-title= suggested) (help)
^ Hosseini, S.; Al Khaled, A. (2014). "A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research". Applied Soft Computing. 24: 1078–1094.
^ Nazari-Shirkouhi, S.; Eivazy, H.; Ghodsi, R.; Rezaie, K.; Atashpaz-Gargari, E. (2010). "Solving the Integrated Product Mix-Outsourcing Problem by a Novel Meta-Heuristic Algorithm: Imperialist Competitive Algorithm". Expert Systems with Applications. 37 (12): 7615–7626. doi:10.1016/j.eswa.2010.04.081.
Duan, H.; Xu, C.; Liu, S.; Shao, S. (2009). "Template matching using chaotic imperialist competitive algorithm". Pattern Recognition Letters. 39 (6): 1362–1381.
Zhang, Yang; Wang, Yong; Peng, Cheng (2009). "Improved Imperialist Competitive Algorithm for Constrained Optimization". Computer Science-Technology and Applications, IFCSTA. {{cite conference}}: Unknown parameter |booktitle= ignored (|book-title= suggested) (help)

Cite error: A list-defined reference named "ica_moslem_2011" is not used in the content (see the help page).
Cite error: A list-defined reference named "Fuzzy_and_Intelligent_Systems_2008" is not used in the content (see the help page).
Cite error: A list-defined reference named "Fuzzy_ICA_2014_NC" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2008_en_conf_rajabioun_decentralized_pid_controller_design_mimo_evaporator" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2008_jnl_atashpaz_ijicc_pid_mimo_distillation_column_process" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2007_cnf_atashpaz_optimal_pid_controller_isfs2007" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2008_en_bchtr_rajabioun_nash_equilibrium_point_achievement" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2009_jnl_atashpaz_decentralized_pid_controller_optimal_shrinkage_gershgorin_bands" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2008_cnf_sepehrirad_recommender_systems" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2009_jnl_khabbazi_minimum_bit_error_rate_beamforming" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_Alikhani_Evaluation_of_Image_Segmentation_Methods" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_cnf_Sayadnavard_Wireless_sensor_network_localization" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2009_jnl_jolai_pareto_simulated_annealing_offline_scheduling_problem_with_rejection" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2010_jnl_shokrollahpour_bi_criteria_flowshop" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_Forouharfard_schedule_cross_docking_systems" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_Karimi_scheduling_flexible_flow_shops_ica_electromagnetic" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_Bagher_Balancing_of_stochastic_U_Type_assembly_lines" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_Sarayloo_ica_Dynamic_Cell_Formation" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2008_jnl_oskouyi_material_properties_characterization_sharp_indentation_test" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2009_cnf_mahmoudi_ann_weights_optimization" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_en_2010_jnl_lucas_linear_induction_motor" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_omid_phev" is not used in the content (see the help page).
Cite error: A list-defined reference named "ica_2010_en_jnl_niknam_k_means_clustering" is not used in the content (see the help page).

Cite error: A list-defined reference named "ica_2010_en_jnl_mozafari_thin_interphase" is not used in the content (see the help page). Category:

Nature-inspired metaheuristics