نتایج جستجو برای: artificial bee colony optimization

تعداد نتایج: 649773  

Journal: :European Journal of Operational Research 2011
Wai Yuen Szeto Yongzhong Wu Sin C. Ho

This paper introduces an artificial bee colony heuristic for solving the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. An enhanced version of the artificial bee colony heuristic is also proposed to improve the solution quality of the original version. The performance of the enhanced h...

2012
Millie Pant Tarun Kumar Sharma D. Karaboga B. Basturk S. Sundar A. Singh

Artificial Bee Colony (ABC) algorithm simulates the foraging behavior of honey bee colonies. ABC is an optimization technique, which is used in finding the best solution from all feasible solutions. However, there is still an insufficiency in ABC regarding improvement in exploitation and convergence speed. In order to improve the performance of ABC we embedded PSO into ABC. As PSO has memory, k...

Journal: :Int. Arab J. Inf. Technol. 2016
Saravanamoorthi Moorthi

There is a trend in the scientific community to model and solve complex optimization process by employing natural metaphors. In this area, Artificial Bee Colony optimization (ABC) tries to model natural behaviour of real honeybees in food foraging. ABC algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm. In this work, ABC is used for solving multivariabl...

2015
Ashay Shrivastava Manish Gupta Shashank Swami Shraddha Saxena Kavita Sharma Savita Shiwani Harish Sharma Amit Singh Neetesh Gupta Nishant Pathak Sudhanshu Tiwari

Artificial Bee Colony (ABC) Algorithm is an optimization algorithm used to find out the global optima. In ABC, each bee stores the information of feasible solution or candidate solution and stochastically modifies this over time, based on the information provided by neighboring bees, it speculative modifies over time and based on the best solution found by the bee itself. . In this proposed wor...

2015
Bhabani Shankar Prasad Mishra Satchidananda Dehuri Sung-Bae Cho

This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems. The fundamental difference of Multiple andMany Objective Optimization problems have been studied very rigorously. The three forefront swarm intelligence methods, i.e., Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony Optimiza...

2017

Grey cast iron of the grade ASTM 48 is in the use for manufacturing casting parts with low or middle duty or load, such as various stove parts, gas burners, boiler parts, protective cover, hand wheel, brackets, base plate, crane balls, counter weight, handle, machine base etc. The production volume rate is mainly lies with the material removal rate during machining process and this is essential...

2014
SHI MEI

Most reservoirs offer a mean of managing and regulating the downstream water flow and demands over time and space. It is a challenging task for the reservoir operator to evaluate the trade-off during drought and heavy rainfall season. This study proposes a review on the application of different computational intelligent models, especially the Artificial Bee Colony (ABC) approach in reservoir in...

2014
Ruchika Malhotra Chand Anand Nikita Jain Apoorva Mittal

One of the essential parts of the software development process is software testing as it ensures the delivery of a good quality and reliable software. Various techniques and algorithms have been developed to carry out the testing process. This paper deals with utility of the nature based algorithms namely Genetic Algorithm, Ant Colony Optimization algorithm and Artificial Bee Colony algorithm i...

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreo...

2012
Xiaoji Yang Zhiguo Huang

This paper presents a new Artificial Bee Colony (ABC) optimization algorithm to solve function optimization problems. The proposed approach is called OCABC, which introduces opposition-based learning concept and dynamic Cauchy mutation into the standard ABC algorithm. To verify the performance of OCABC, eight well-known benchmark function optimization problems are used in the experiments. Exper...

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