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1
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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3
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The objective functions are loss of load probability (LLP) and life cycle cost (LCC) and levelized cost of energy (LCE). …”
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4
Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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5
A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…The minimum values of these objective functions enable a trajectory to be drilled with minimum drilling cost and maximum safety. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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7
A Kalman-Filter-Based Sine-Cosine Algorithm
Published 2019“…The algorithm is tested with various benchmark functions and compared with the original SCA algorithm. …”
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Genetic algorithms for urban transit routing problems
Published 2012“…The proposed algorithm is ¯rst applied to the single objective of UTRP which involves only the passengers' cost. …”
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9
Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems
Published 2024“…This paper explores the tuning of the Sigmoid Proportional-Integral-Derivative (SPID) controller using variations of the Smoothed Functional Algorithm (SFA) for the underactuated Multiple-Input Multiple-Output (MIMO) twin-rotor system. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…The results show that the ABRO algorithm outperforms the original ABC algorithm and ARO algorithm in all benchmark functions and successfully reduces the cost of the power generation for the IEEE- 26 bus system.…”
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A comparative study on testing optimization techniques with combinatorial interaction testing for optimizing software product line testing
Published 2025“…An experiment has been conducted on the most commonly used optimization algorithms in previous studies. The optimization algorithms we explored are the Genetic Algorithm, Cuckoo Search algorithm, Ant Colony algorithm, and Particle Swarm Optimization algorithm. …”
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Stochastic optimal control of economic growth model under research and development investment with Kalman filtering approaches
Published 2022“…Moreover, the optimal control policy based on the state estimate generated from the UKF could optimize the cost function of the problem. Hence, the results show the efficiency of the algorithms proposed. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…The research methodology involves problem modeling, algorithm development, and validation. The TSP concept formulated the MDMT problem, representing holes as cities and tools as a salesman in finding the shortest path to develop a mathematical model or fitness function. …”
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15
Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…The HFPSO algorithm is a hybridization of the Firefly Optimization (FFO) and the Particle Swarm Optimization (PSO) technique, to enhance the exploration, exploitation strategies, and to speed up the convergence rate. …”
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Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim
Published 2006“…This study will utilize concept of Immune Evolutionary Programming (IEP) which is a combination of EP and AIS technique and compare the results to that obtained from Evolutionary Programming (EP) technique. The study explores two functions namely total loss minimization and total cost minimization as the objective fimction. …”
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17
Exploration of educational building with cultural elements using shape grammar
Published 2013“…This research explores the application of shape grammars in generating educational building designs with cultural, functional and artistic issues. …”
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Undergraduates Project Papers -
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Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan
Published 2024“…Industrial applications also focus on maximizing efficiency and minimizing costs. This research explores the application of the Scaled Conjugate Gradient (SCG) method, utilizing a strong Wolfe line search, in the context of portfolio selection. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Although useful, the existing algorithms does not provide any comparative data to select an algorithm based on the problem size and difficulty and the use of other neighborhood algorithms (including Great Deluge and Late Acceptance Hill Climbing) has not been sufficiently explored as well. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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