Artificial bee colony algorithm

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1 - FA-ABC: A Novel Combination of Firefly Optimization Algorithm and Artificial Bee Colony for Mathematical Test Functions and Real-World Problems
Ali reza Shafiee sarvestany Mohammadjavad Mahmoodabadi

10.30486/admt.2022.1940026.1314

In this research study, an attempt is made to present a new optimization scheme by combination of the firefly algorithm and artificial bee colony (FA-ABC) to solve mathematical test functions and real-world problems as best as possible. In this regard, the main operator چکیده کامل

In this research study, an attempt is made to present a new optimization scheme by combination of the firefly algorithm and artificial bee colony (FA-ABC) to solve mathematical test functions and real-world problems as best as possible. In this regard, the main operators of the two meta-heuristic algorithms are employed and combined to utilize both advantages. The results are compared with those of five prominent well-known approaches on sixteen benchmark functions. Moreover, thermodynamic, economic and environmental modeling of a thermal power plant known as the CGAM problem is represented. The proposed FA-ABC algorithm is used to reduce the total cost and increase the efficiency of the system as shown in the Pareto front diagrams. پرونده مقاله

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2 - The combinatorial of Artificial Bee Colony algorithm and Bisection method for solving Eigenvalue Problem
Parvaneh Mansouri

The aim of this paper is to find eigenvalues of square matrix A based on the Artificial Bee Colony algorithm and the Bisection method(BIABC ). At first, we obtain initial interval [a,b] that included all eigenvalues based on Gerschgorin's theorem, and then by using Arti چکیده کامل

The aim of this paper is to find eigenvalues of square matrix A based on the Artificial Bee Colony algorithm and the Bisection method(BIABC ). At first, we obtain initial interval [a,b] that included all eigenvalues based on Gerschgorin's theorem, and then by using Artificial Bee Colony algorithm(ABC) at this interval to generate initial value for each eigenvalue. The bisection method improves them until the best values of eigenvalues with arbitrary accuracy will be achieved. This enables us to find eigenvalues with arbitrary accuracy without computing the derivative of the characteristic polynomial of the given matrix. We illustrate the proposed method with Some numerical examples. پرونده مقاله

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3 - The Iterative Method for Solving Non-Linear Equations
Parvaneh Mansouri

In this paper, we have combined the ideas of the False Position (FP) and Artificial Bee Colony (ABC) algorithms to find a fast and novel method for solving nonlinear equations. Additionally, to illustrate the efficiency of the proposed method, several benchmark function چکیده کامل

In this paper, we have combined the ideas of the False Position (FP) and Artificial Bee Colony (ABC) algorithms to find a fast and novel method for solving nonlinear equations. Additionally, to illustrate the efficiency of the proposed method, several benchmark functions are solved and compared with other methods such as ABC, PSO and GA. پرونده مقاله

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4 - Locating Optimal Places for Emergency Medical Centers Using Artificial Bee Colony Algorithm
Karim Mohrechi Abdolreza Hatamlou

The Emergency Medical Centers are very helpful since they reduce the number of death and injuries by getting to the scenes of accidents and dealing with the case immediately. As saving one's life is the prime goal in these centers, any findings and techniques which will چکیده کامل

The Emergency Medical Centers are very helpful since they reduce the number of death and injuries by getting to the scenes of accidents and dealing with the case immediately. As saving one's life is the prime goal in these centers, any findings and techniques which will improve the services and ease achieving the goal will be highly welcomed. The first and the major factor in giving this kind of service is the time. The place where these centers are located can play an important role to reduce the time so as to offer the service right away and on time. Hence, finding the best places in a big city or cities to set up these centers to be able to give the services urgently will have a crucial importance. The method offered in this paper is to give the service qualitatively while we reduce the number of ambulances. Artificial bee colony (ABC) algorithm is an extended algorithm based on the bees' vigilant behavior that they search for food. This paper uses The ABC algorithm to solve the problem of positioning. The findings and the correlative coefficient of the study show that this Algorithm can be helpful especially in larger cities where it is difficult to locate a proper position to offer the service in an expected time. پرونده مقاله

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5 - Diagnosis of Brain Tumor Position in Magnetic Resonance Images by Combining Bounding Box Algorithms, Artificial Bee Colonies and Grow Cut
Mahdi Shafiof Neda Behzadfar

Tumor detection and isolation in magnetic resonance imaging (MRI) is a significant consideration, but when done manually by people, it is very time consuming and may not be accurate. Also, the appearance of the tumor tissue varies from patient to patient, and there are چکیده کامل

Tumor detection and isolation in magnetic resonance imaging (MRI) is a significant consideration, but when done manually by people, it is very time consuming and may not be accurate. Also, the appearance of the tumor tissue varies from patient to patient, and there are similarities between the tumor and the natural tissue of the brain. In this paper, we have tried to provide an automated method for diagnosing and displaying brain tumors in MRI images. Images of patients with glioblastoma were used after applying pre-processing and removing areas that have no useful information (such as eyes, scalp, etc.). We used a bounding box algorithm, to create a projection for to determining the initial range of the tumor in the next step, an artificial bee colony algorithm, to determine an initial point of the tumor area and then the Grow cut algorithm for, the exact boundary of the tumor area. Our method is automatic and extensively independent of the operator. comparison between results of 12 patients in our method with other similar methods indicate a high accuracy of the proposed method (about 98%) in comparison s. پرونده مقاله

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6 - بهینه‌سازی سبد چند نوع دارایی براساس ارزش در معرض ریسک شرطی با استفاده از الگوریتم کلونی مصنوعی زنبورعسل
سمیه السادات موسوی عباسعلی جعفری ندوشن مرضیه کاظمی راشنانی مهسا محمدطاهری

مدیریت و بهینه‌سازی سبدی متشکل از انواع دارایی با هدف افزایش بازده و کاهش ریسک، همواره مورد توجه سرمایه‌گذاران بوده‌ است. باتوجه به تورم در بازار ایران، عملکرد متفاوت دسته‌های دارایی در شرایط مختلف بازار و قابلیت کسب سود بیشتر به همراه ریسک کمتر با متنوع‌سازی انواع دارا چکیده کامل

مدیریت و بهینه‌سازی سبدی متشکل از انواع دارایی با هدف افزایش بازده و کاهش ریسک، همواره مورد توجه سرمایه‌گذاران بوده‌ است. باتوجه به تورم در بازار ایران، عملکرد متفاوت دسته‌های دارایی در شرایط مختلف بازار و قابلیت کسب سود بیشتر به همراه ریسک کمتر با متنوع‌سازی انواع دارایی، تشکیل سبدی متشکل از سهام، ارز و کالا ضروری به ‌نظر می‌رسد. در این مقاله دارایی‌هایی از دسته-هایی شامل سکه امامی، دلار آمریکا و 11 شاخص‌ سهام بخش‌های مختلف صنعت در ترکیب سبد در نظرگرفته ‌شده‌‌است. با توجه به اهمیت سنجه ریسک در بهینه‌سازی سبد چند نوع دارایی، مدلی براساس ارزش در معرض ریسک شرطی با رویکرد شبیه‌سازی تاریخی توسعه ‌داده‌‌شده، کارایی آن با مدل میانگین-واریانس مقایسه‌ شده و برای حل مدل‌ها دو الگوریتم کلونی مصنوعی زنبورعسل و رقابت استعماری بکارگرفته‌شد. برای ارزیابی مدل‌ها در بازار ایران، از سری زمانی قیمت روزانه دارایی‌ها در بازه 1392 الی 1398 استفاده شد. نتایج حاصل از مقایسه دو مدل در دوره‌های آموزش و تست نشان‌ داد، در بهینه‌سازی سبد انواع دارایی مدل میانگین-ارزش درمعرض ریسک شرطی از میانگین-واریانس عملکرد بهتری دارد. از طرفی براساس نسبت‌های شارپ، شارپ شرطی و بازده به ریسک، سبد‌های بهینه‌شده با الگوریتم کلونی مصنوعی زنبورعسل بهتر از الگوریتم رقابت استعماری هستند. پرونده مقاله

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