Global ETD Search
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 15 of 15 for “"Evolutionary computing"”.
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Evolutionary computing for routing and scheduling applications
… regarding scheduling, routing optimization and evolutionary algorithms by referring to recent literatures. In depth depiction about research work includes the design of an evolutionary algorithm to solve vehicle routing problem with time windows (VRPTW) which is a case study of vehicle …
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Automatic control program creation using concurrent Evolutionary Computing
… output solution using a custom low -level evolutionary language set, combining both continuous and Boolean data types. The system uses a multi -tasking model to evolve and execute the required LGP code for each system output using separate populations: Two example problems -a simple fridge …
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Evolutionary computing techniques to aid the acquisition and analysis of nuclear magnetic resonance data
Evolutionary computation, including genetic algorithms and genetic programming have taken the ideas of evolution in biology and applied some of the characteristics to problem solving. The survival of the fittest paradigm allows a population of candidate solutions to be modified by sexual and …
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Pagenumber problem.
… two dimensional pagenumber models are proposed. Evolutionary computing methods on problems whose solution space comprises of permutations are reviewed. Since the pagenumber problem is known to be NP-complete, we describe two solutions using Hill Climbing methods and one solution using Genetic …
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Learning Strategies in Multi-Agent Systems - Applications to the Herding Problem
… been proposed such as reinforcement learning and evolutionary computing. In this thesis two solutions to a multi-agent herding problem are presented. One solution is based on Q-learning algorithm, while the other is based on modeling of artificial immune system. Q-learning solution for the herding …
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Nature-Inspired Multi-Objective Optimisation and Transparent Knowledge Discovery via Hierarchical Fuzzy Modelling
… (interpretable) fuzzy systems with robust evolutionary computing based algorithms involving several techniques, such as data clustering, data mining, and multi-objective optimisation. Evolutionary optimisation algorithms are also developed on the basis of nature and social inspired ideas. …
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Spectral analysis of neutral evolution
… by a detailed review of the literature in both evolutionary computing and biology concerning the structure of neutral networks. This is extended by studying the actual and predicted population distribution over the neutral networks of H1N1 and H3N2 influenza haemagglutinin during seasons between …
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On the Simultaneous Perception of Sound and Three-Dimensional Objects
… Using the concept of the search space from evolutionary computing as an example, the case is made that multimedia artworksde can present a larger field of creative opportunity than single-media works, due to the enhanced interplay between the two media and the viewer's a priori knowledge. …
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Evolutionary polymorphic neural networks in chemical engineering modeling
Evolutionary Polymorphic Neural Network (EPNN) is a novel approach to modeling chemical, biochemical and physical processes. This approach has its basis in modern artificial intelligence, especially neural networks and evolutionary computing. EPNN can perform networked symbolic regressions for …
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Computation Approaches for Continuous Reinforcement Learning Problems
… non-linear and over-complicated systems. Evolutionary Computing (EC) methods exploit nature’s way by imitating the evolution process and avoid to solve the control problem analytically. Reinforcement Learning (RL) from the other side regards the optimal control problem as a sequential one. …
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Explainability of non-deterministic solvers: explanatory feature generation from the data mining of the search trajectories of population-based metaheuristics.
Evolutionary algorithms (EAs) are the principal focus of research study in Evolutionary Computing (EC). In EC, naturally occurring processes designed to drive success in nature are simulated for a similar purpose in numerical optimisation. Such processes include natural selection, genetic mutation …
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Rules of engagement: competitive coevolutionary dynamics in computational systems
Given that evolutionary biologists have considered coevolutionary interactions since the dawn of Darwinism, it is perhaps surprising that coevolution was largely overlooked during the formative years of evolutionary computing. It was not until the early 1990s that Hillis' seminal work thrust …
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Meta Concepts: A Knowledge-Based Code Generation System
People have an amazing ability to solve complex problems by performing a sequence of simpler operations (i.e: functions/procedures which take input variables and produce output variables). We are able to do so even when there exists a large number of possible choices for such operations and when …