Search Results - (( develop some solutions algorithm ) OR ( java implication based algorithm ))
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Comparison Between Genetic Algorithm and Electromagnetism-Like Algorithm for Solving Inverse Kinematics
Published 2012“…Self developed software simulator is used to display some of these solutions at each goal position.…”
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Overview of metaheuristic: classification of population and trajectory
Published 2010“…Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. …”
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Monograph -
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm gives a pool of solutions rather than just one. …”
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Meta-heuristic structure for multiobjective optimization case study: Green sand mould system
Published 2014“…Some comparative analyses are then carried out with the algorithms developed and employed in this work. …”
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Kinematic contact-impact algorithm with friction
Published 2001“…To validate the developed contact-impact algorithm, some numerical examples are illustrated. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. HOGA (Hybrid Optimization by Genetic Algorithms) is developed by Dr.Lopez from Zaragoza university in Spain. …”
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Normal-boundary intersection based parametric multi-objective optimization of green sand mould system
Published 2013“…Some comparative studies were then carried out with the algorithms developed and used in this work and that from some previous work. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…There have been several scientific investigations in the past several decades on discovering effective and efficient algorithms to providing solutions to the optimization needs of mankind leading to the development of deterministic algorithms that provide exact solutions to optimization problems. …”
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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
Published 2014“…The Hypervolume Indicator (HVI) is applied to gauge the capabilities of each algorithm in approximating the Pareto frontier. Some comparative studies are then carried out with the algorithms developed in this chapter. …”
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…However, there is no applications of MTS in UTSP are known to date. Therefore, MTS is developed from TS with some additional features such as systematic neighbourhood evaluation procedure to reach the near optimal solutions quickly. …”
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An Efficient Ranking Analysis In Multi-Criteria Decision Making
Published 2017“…Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. …”
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A COMPUTATIONAL ALGORITHM for the NUMERICAL SOLUTION of NONLINEAR FRACTIONAL INTEGRAL EQUATIONS
Published 2022“…In this paper, we develop a numerical method for the solution of nonlinear fractional integral equations (NFIEs) based on Haar wavelet collocation technique (HWCT). …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
Published 2010“…A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. …”
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