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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Meta-heuristic algorithms"”.
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Optimal distribution network reconfiguration using meta-heuristic algorithms
… added to the distribution network. The heuristic optimization algorithm which is proposed in Chapter 3 and is improved in Chapter 5 is implemented on a smaller case study in Chapter 6 to demonstrate that the identified solution through the optimization process is the same with the …
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Enhancing meta-heuristic algorithms using center-based sampling at population level
… to enhance the efficiency and effectiveness of meta-heuristic algorithms. The strategy of center-based sampling can be utilized at either the operation and/or population levels. Despite the overall efficiency of the center-based sampling in population-based algorithms, utilization at the …
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Hybrid Meta-heuristic Algorithms for Static and Dynamic Job Scheduling in Grid Computing
… This thesis studies the application of hybrid meta-heuristics to the job scheduling problem in grid computing, which is recognized as being one of the most important and challenging issues in grid computing environments. Similar to job scheduling in traditional computing systems, this …
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Definition of a Common Formulation of Military Frequency Assignment Problems and the Application of Meta-Heuristic Algorithms
… in a form which allows the application of meta-heuristic algorithms. Currently different frequency assignment systems are in use in the four areas of the military, in the categories of land, air, maritime and satellite. The tasks are to define the common aspects of the relevant frequency …
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Optimization Models and Algorithms for Spatial Scheduling
… time. Accordingly, two classes of approximation algorithms were developed: greedy heuristics for finding fast, feasible solutions; and hybrid meta-heuristic algorithms to search for near-optimal solutions. A flexible hybrid algorithm framework was developed, and a number of hybrid algorithms were …
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Optimal consignment stocking policies for a supply chain under different system constraints
… variables being considered. Three doubly-hybrid meta-heuristic algorithms that combine two different hybrid meta-heuristic algorithms are developed to provide a solution procedure for the rest of models. Numerical experiments illustrate the solution procedures and reveal the effects of the …
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Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence.
… the use of evolved Bayesian networks learning algorithms based on computational intelligence meta-heuristic algorithms. These algorithms are applied to a new domain provided by the exclusive data, available to this project from an industry partnership with ODS-Petrodata, a business intelligence …
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Digital Filter Design Using Improved Artificial Bee Colony Algorithms
… and group delay responses. Evolutionary algorithms are population-based meta-heuristic algorithms inspired by the biological behaviors of species. Compared to gradient-based optimization algorithms such as steepest descent and Newton’s like methods, these bio-inspired algorithms have the …
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Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization
… developed, based on computer experiments with meta-heuristic algorithms. Most of these meta-heuristics implement some sort of stochastic search method, amongst which the 'Evolutionary Algorithm' is garnering much attention. It possesses several characteristics that make it a desirable method …
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Disaster recovery planning of transportation networks
… of DRPTN modeling would benefit from adopting meta-heuristic algorithms when explicit or implicit justifications exist, such as convexity, linearity, or complexity analysis of the mathematical programming. In the problem formulation phase, more effort could integrate traffic management measures …
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Entropy-based framework for combinatorial optimization problems and enabling the grid of the future
… parts. In the first part, I describe efficient meta-heuristic algorithms for a series of combinatorially complex optimization problems, while the second part is concerned with robust and scalable control architecture for a network of paralleled converter/inverter systems (DC/AC microgrids). …