نتایج جستجو برای: Artificial Bee Colony Algorithm

تعداد نتایج: 1058027  

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده برق و الکترونیک 1390

there are many approaches for solving variety combinatorial optimization problems (np-compelete) that devided to exact solutions and approximate solutions. exact methods can only be used for very small size instances due to their expontional search space. for real-world problems, we have to employ approximate methods such as evolutionary algorithms (eas) that find a near-optimal solution in a r...

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effect...

Journal: :journal of advances in computer research 2015
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 improve the services and ease achieving the goal will be highly welcomed. the first and the major factor in giving this kind o...

2014
Rodrigo Cuesta Broderick Crawford Ricardo Soto Fernando Paredes

In this paper, we present a new Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent metaheuristic technique based on the intelligent foraging behavior of honey bee swarm. Computational results show that Artificial Bee Colony algorithm is competitive in terms of solution quality with other metaheuristic approaches for the...

2015
M Abdullah

Grid computing is a new computing model; it’s performing bulk operations among the connected network. Since it is possible to run multiple applications simultaneously may require multiple resources but often do not have the resources that time scheduling system is essential for allocating resources. Scheduling algorithms must be designed for Maximize utilization of the resources and minimize th...

2009
Jiann-Horng Lin Li-Ren Huang

Artificial Bee Colony algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. This paper presents Bee Swarm Optimization intended to introduce chaotic sequences and psychology factor of emotion into the algorithm. We define two emotions Bees could have, positive and negative, and correspond to two reaction to perception respectively. For avoiding premature c...

2010
Dervis Karaboga Celal Ozturk

In this work, performance of the Artificial Bee Colony Algorithm which is a recently proposed algorithm, has been tested on fuzzy clustering. We applied the Artificial Bee Colony (ABC) Algorithm fuzzy clustering to classify different data sets; Cancer, Diabetes and Heart from UCI database, a collection of classification benchmark problems. The results indicate that the performance of Artificial...

2015
Pankaj Sharma Sandeep Tiwari Manish Gupta X. Yan C. Zhang Mohit K. Gupta Amit Singh Neetesh Gupta

In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the...

2014
Broderick Crawford Ricardo Soto Wenceslao Palma Franklin Johnson Fernando Paredes Eduardo Olguín

We present a novel application of the Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on the intelligent foraging behavior of honey bees. We present a 2-level metaheuristic approach where an Artificial Bee Colony Algorithm acts as a low-level metaheuristic and its paremeters are se...

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