Search Results - (( solution population optimisation algorithm ) OR ( java application testing algorithm ))
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Optimisation of multi-stage production-inspection stations using genetic algorithm
Published 2000“…The optimisation tool to be considered is Genetic Algorithm (GA). …”
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Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems
Published 2016“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm, and Genetic Algorithm (GA). …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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6
Multi-population Genetic Algorithm for Rich Vehicle Routing Problems
Published 2020“…In this pa�per we present Multi-population Genetic Algorithm for Rich Vehicle Routing Prob�lems (MPGA-RVRP) to provide diversity and delay premature convergence in GA by making use of multiple populations that share potential solutions among each other and evolve independently optimising only one objective. …”
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Fuzzy genetic algorithms for combinatorial optimisation problems
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Hybrid genetic algorithm for uncapacitated university examination timetabling problem
Published 2015“…The PGA will then hybridised with three new local optimisation techniques, which will make up the HGA; to improve the solutions found. …”
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Hybrid genetic algorithm for university examination timetabling problem
Published 2016“…The main components of the genetic operators in a GA will be tested and the best combination of the genetic operators will be adopted to construct a Pure Genetic Algorithm (PGA). The PGA will then hybridised with three new local optimisation techniques, which will make up the HGA; to improve the solutions found. …”
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Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad
Published 2018“…The performance of the proposed approach is evaluated by comparing it with four population-based approaches and an existing hyper-heuristic approach named Hyper-Heuristic Scheduling Algorithm (HHSA). …”
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Varying Variants For AncDE With MDV Between Target And Trial Vector Measurement
Published 2018“…This paper compares standard Differential Evolution algorithm with AncDE,which adds a separate cache of recent ancestors that serve as an additional source of highquality genetic information.We compare the solutions produced by both DE and AncDE algorithms using benchmarks of 15 different numeric optimisation problems.Two distinct explorations are presented.The first test is distinct algorithmic variants of AncDE.The second part of this paper defines an MDV attribute and results are presented indicating some interesting differences in MDV between the DE and AncDE algorithms.Our findings indicate that ancestors can help to overcome some of the local variations in solutions quality and improve solution quality by improving population diversity.…”
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Power generation allocation in smart grid using Dwarf Mongoose Optimization / Mohamad Irfan Shamani
Published 2025“…The results show that the population size on mongoose is an important factor in finding optimal solution. …”
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Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
Published 2010“…University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling problem. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. …”
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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List
Published 2023“…In the proposed technique, deterministic PL technique is applied to produce a population of initial solutions. The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Optimizing palm oil biomass collection: genetic algorithm approaches in solving location-routing problem
Published 2025“…To achieve these objectives, the research employs genetic algorithm (GA) approaches, incorporating innovative strategies, namely automated mutation operator selection (AMOS) and elite child population (ECP). …”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…In the proposed technique, deterministic PL technique was first applied to produce a population of initial solutions. The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud
Published 2021“…Our proposed algorithm is an extension of the standard symbiotic organism search (SOS), a nature-inspired algorithm that has been implemented to solve various numerical optimisation problems. …”
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