nonlinear optimization based algorithm
A Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems
... has been proposed by Kennedy, et al [12]. The development of PSO was based on observations of animals, social behavior such as birds flocking and fish schooling. PSO is initialized with a population of random ...
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Magnetic localization and orientation of the capsule endoscope based on a random complex algorithm
... and algorithm. In this paper, based on the magnetic dipole model as well as magnetic sensor array, we propose nonlinear optimization algorithms using a random complex algorithm, applied ...
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A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
... chaos optimization algorithm (PCOA) using logistic map and outlook algorithm, a hybrid global optimization algorithm (PCOOA) is ...The algorithm is structured in two ...chaos ...
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Research Article Heuristic-Based Firefly Algorithm for Bound Constrained Nonlinear Binary Optimization
... local optimization procedures and therefore there is no guarantee that a global solution is ...global optimization, stochastic methods are generally used and aim to explore the search space and converge to ...
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A Solution to Economic Dispatch Problem Using Augmented lagrangian Particle Swarm Optimization
... mathematical optimization methods, such as Dynamic programming, lambda method, gradient method, and Newton ...many optimization techniques for solving ELD problem such as fuzzy, GA, hybrid techniques etc ...
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Optimization of a new digital image compression algorithm based on nonlinear dynamical systems
... P a g e | 36 in which A is always followed byy B and vice vversa. If the probabilistiic model con nsiders indivvidual letters as independe ent, the enttropy rate of o the se[r] ...
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EHPSO: An Enhanced Hybrid Particle Swarm Optimization Algorithm for Internet of Things
... completion algorithm using a nonlinear conjugate gradient method was proposed in ...stitching based distributed algorithms were depicted in ...localization algorithm was described in [8]. A ...
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On the optimization of Dombi non-linear programming
... linear optimization problem in which the constraints are de- fined as fuzzy relational equations (FRE) with the Dombi family of ...conventional nonlinear programming methods may not be directly em- ployed ...
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An Efficient Continued Fraction Algorithm for Nonlinear Optimization and Its Computer Implementation
... iterative algorithm for the problem based on the continued fraction interpolation ...the algorithm constructs the n + 1th point according to the information given by the previous n ...the ...
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Motion Planning for Highly Automated Road Vehicles with a Hybrid Approach Using Nonlinear Optimization and Artificial Neural Networks
... planning algorithm is that it must be computable fast enough to enable real-time application on state of the art ...geometric based methods, graph search based algorithms, incremental search ...
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A Hybrid AANN-KPCA Approach to Sensor Data Validation
... for nonlinear principal component analysis are com- ...to nonlinear component mapping of a given set of data obtained from a nonlinear quasi-static ...
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The Newton-like properties of the updating mechanism of a model-reality differences algorithm
... this algorithm plays an important role in determining the convergence rate of the ...main algorithm by partitioning DISOPE into two distinct sub procedures based on theorems of composite ...DISOPE ...
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A Tabu Search hyper heuristic strategy for t way test suite generation
... Within HHH, the three defined operators (i.e. improvement, intensification and diversification operators) serve as the virtual “switch” for HHH. Achieving balance diversification and intensification through diversity ...
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Comparative Analysis of Meta-Heuristic Algorithms based on their Application Areas in SRGM
... this algorithm is overstated with the help of the introductory principles of the given parameters that are utilized in the weighing process of the cognitive & communal mechanism including weighing approach of ...
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The Discrete Particle Swarm Optimization Algorithms For Permutation Flowshop Scheduling Problem
... swarm optimization (DPSO) algorithms are presented to solve the Permutation Flow Shop Scheduling Problem ...developed based on the discrete domain because PFSP is represented as discrete job ...proposed ...
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APPLICATIONS OF ARTIFICIAL INTTELEGENCE APPPROCH IN MACHINIG OPERATIONS
... swarm optimization (PSO) based on the analogy of swarm of bird and school of ...The algorithm, which is based on a metaphor of social interaction, searches a space by adjusting the ...
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An Augmented Lagrangian Algorithm for Engineering Optimization by Solving Nonlinear Programming Problem
... We use the method of multipliers as an approach for solving NLP problems using augmented Lagrangian penalty function. Consider the problem (P) subject to the equality constraints g i (x) = 0 for i∈I, the condition (2*) ...
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Optimization Algorithm of Fireworks Explosion Based on Genetic Algorithm
... Fireworks algorithm is a kind of parallel explosive search method by introducing random factors and selection strategy, which is developed into an optimization algorithm with strong ...
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Design Optimization Average-Based Algorithm
... In optimization, there is traditionally a concern with developing a good stopping ...an algorithm with a guaranteed level of accuracy seems doomed to failure in general stochastic search ...
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A diverse versions and variations of Particle Swarm Optimization (PSO) algorithm for real world complex optimization problems
... PSO is a population based cooperative search.PSO satisfies the local optimization but it is hard to express the robustness because of its iteration ability. In order to reduce the iteration, the operator ...
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