Search Results - (( development using meta algorithm ) OR ( java simulation optimization algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
Get full text
Get full text

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of 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 existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
Get full text
Get full text
Get full text

Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text

Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni

“…Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni…”
Get full text

Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

“…Many meta-heuristic algorithms have been developed to date (e.g. …”
Get full text
Get full text
Get full text

OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Proposal of meta-requirement approach to analyze requirements specification completeness by Muhamad Idaham, Umar Ong, M. A., Ameedeen

“…The objectives of this research are to identify the major factors in validating user requirements, development of a reverse engineered meta-requirement algorithm and validating with expert panel in requirements engineering of the algorithm usefulness. …”
Get full text
Get full text

Meta-requirement method towards analyzing completeness of requirements specification by Muhamad Idaham, Umar Ong, Mohamed Ariff, Ameedeen, Imran Edzereiq, Kamarudin

“…However, due to time constraint, requirements validation steps are commonly ignored by developer. The objectives of this research are to identify the major factors in validating user requirements, development of a reverse engineered meta-requirement algorithm and validating with expert panel in requirements engineering of the algorithm usefulness. …”
Get full text
Get full text
Get full text

Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
Get full text
Get full text

An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm by Najeeb M., Mansor M., Feyad H., Taha E., Abdullah G.

“…This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (Kp, Kt) automatically. …”

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
Get full text
Get full text

Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation by Hasneeza Liza, Zakaria

“…Although useful, much existing meta-heuristic based strategies have not sufficiently explored the adoption of more than one meta-heuristic to perform the search (termed hybridization). …”
Get full text
Get full text

Meta-heuristic structure for multiobjective optimization case study: Green sand mould system by Ganesan, T., Elamvazuthi, I., KuShaari, K.Z., Vasant, P.

“…Analysis on the solution set produced by these algorithms is carried out using performance metrics. …”
Get full text
Get full text

Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

Get full text
Get full text
Get full text

A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
Get full text
Get full text
Get full text

Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic by Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim

Get full text
Get full text

Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
Get full text
Get full text

Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim by Abdul Rahim, Siti Rafidah

“…In this study, Meta Evolutionary–Firefly Algorithm (EMEFA) was initially developed to expedite the computational time in multi-DG installation with improved accuracy. …”
Get full text
Get full text

Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…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.…”
Get full text
Get full text
Get full text
Get full text

An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
Get full text
Get full text
Get full text
Get full text