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Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects
Joint Authors
Houtinezhad, Maryam
Ghaffari, Hamid Rida
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 3 (31 May. 2021), pp.261-269, 9 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-05-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Economics & Business Administration
Abstract EN
The goal of optimizing the best acceptable answer is according to the limitations and needs of the problem.
For a problem, there are several different answers that are defined to compare them and select an optimal answer; a function is called a target function.
The choice of this function depends on the nature of the problem.
Sometimes several goals are together optimized; such optimization problems are called multi-objective issues.
One way to deal with such problems is to form a new objective function in the form of a linear combination of the main objective functions.
In the proposed approach, in order to increase the ability to discover new position in the Imperialist Competitive Algorithm (ICA), its operators are combined with the particle swarm optimization.
The colonial competition optimization algorithm has the ability to search global and has a fast convergence rate, and the particle swarm algorithm added to it increases the accuracy of searches.
Inthis approach, the cosine similarity of the neighboring countries is measured by the nearest colonies of an imperialist and closest competitor country.
In the proposed method, by balancing the global and local search, a method for improving the performance of the two algorithms is presented.
The simulation results of the combined algorithm have been evaluated with some of the benchmark functions.
Comparison of the results has been evaluated with respect to metaheuristic algorithms suchm as Differential Evolution (DE), Ant Lion Optimizer (ALO), ICA, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA).
American Psychological Association (APA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. 2021. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology،Vol. 18, no. 3, pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
Modern Language Association (MLA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology Vol. 18, no. 3 (May. 2021), pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
American Medical Association (AMA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 3, pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 276-179
Record ID
BIM-1432093