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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem
Published 2010“…This research not only analyzes the MACL problem with a mathematical model and genetic algorithm (GA) and the Bees Algorithm but also it make a comparison among the mathematical models to measure the efficiency of the stated algorithm in solving the number of tardy jobs concept and also adds original aspects, the Cell Formation, the traditional GA methods. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…In this simulation, onlooker bees as the important bee make decision to choose the specific method. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…The algorithm, which is a swarm-based algorithm inspired by the food foraging behavior of honey bees, was also employed to select the components making up the feature vectors to be presented to the SVM. …”
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Assembly sequence optimization using the bees algorithm
Published 2022“…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
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Artificial bee colony for inventory routing problem with backordering
Published 2014“…We run the algorithm on a set of benchmark problems and the results are very encouraging.…”
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Economic and emission load dispatch solution via artificial bee colony algorithm
Published 2017“…This paper investigates the performances of Artificial Bee colony (ABC) algorithm for determining optimal solution for EELD problem. …”
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Bee foraging behaviour techniques for grid scheduling problem
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
Published 2018“…However, the existing fire evacuation routing models using various algorithm such as ant colony optimization or particle swarm optimization can neither properly interpret the delay caused by congestion during evacuation nor determine the best layout of emergency exit guidance signs; thus bee colony optimization is expected to solve the problem. …”
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Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms
Published 2015“…Furthermore, to make the algorithms more effective, Taguchi method is employed to tune various parameters of the proposed algorithms. …”
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization
Published 2021“…The fitness-dependent optimizer (FDO), a newly proposed swarm intelligent algorithm, is focused on the reproductive mechanism of bee swarming and collective decision-making. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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ABC Algorithm for Combinatorial Testing Problem
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Optimize single line to ground fault detection in distribution grid power system using artificial bee colony
Published 2023“…ABC intelligently optimizes many mathematical problems. ABC with network neural artificial intelligence (AI) improves algorithm performance (artificial bee colony network neural (ABCNN)). …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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