Search Results - (( solution population optimisation algorithm ) OR ( java implication based algorithm ))

Optimisation of multi-stage production-inspection stations using genetic algorithm by Hassan, Azmi, Pham, Duc Trung

“…The optimisation tool to be considered is Genetic Algorithm (GA). …”
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Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

“…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 by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…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 by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…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 by Almazini, Hussein

“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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Multi-population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, Joseph Mabor

“…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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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

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Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

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Hybrid genetic algorithm for uncapacitated university examination timetabling problem by Ishak, Suhada

“…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 by Ishak, Suhada, Lee, Lai Soon, Ibragimov, Gafurjan

“…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 by Ehab Nabiel , Mohammad

“…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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Varying Variants For AncDE With MDV Between Target And Trial Vector Measurement by Abal Abas, Zuraida, Mohd Salleh, Siti Khadijah, O’Donoghue, Diarmuid, Shibghatullah, Abd Samad

“…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 by Shamani, Mohamad Irfan

“…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 by Al-Betar, Mohammed Azmi

“…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 by Othman M.N.C., Rahman T.K.A., Mokhlis H., Aman M.M.

“…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. …”

Optimizing palm oil biomass collection: genetic algorithm approaches in solving location-routing problem by Foo, Fong Yeng, Zaitul Marlizawati Zainuddin, Hang, See Pheng

“…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 by Che Othman, Muhammad Nazree

“…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 by Sa’ad, Suleiman, Muhammed, Abdullah, Abdullahi, Mohammed, Abdullah, Azizol, Ayob, Fahrul Hakim

“…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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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

“…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. …”
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A performance of AFIRO among asynchronous iteration strategy metaheuristic algorithms by Ab Rahman, Tasiransurini, Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim

“…Asynchronous Finite Impulse Response Optimizer (AFIRO) is a metaheuristic algorithm that has been developed as a population-based solution with an asynchronous update mechanism. …”
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