Titlebook: Evolutionary Algorithms in Engineering Applications; Dipankar Dasgupta,Zbigniew Michalewicz Book 1997 Springer-Verlag Berlin Heidelberg 19

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A Genetic Algorithm Approach for River Managementution of such problems requires both a detailed model of the system and a powerful optimization technique. Standard approaches often represent a trade-off between model accuracy and optimization capability. When a large system is modeled in detail, optimization techniques such as dynamic programming

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The Identification and Characterization of Workload Classesew bridge design, what would be the effect of 10 large trucks simultaneously crossing the bridge? Or, for an existing parallel computer system, what would be the expected response time if three processors failed simultaneously? To be able to answer such performance prediction questions, an engineer

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Lossless and Lossy Data Compression[7, 14, 15]. Lossless compression is used where perfect reproduction is required while lossy compression is used where perfect reproduction is not possible or requires too many bits. Achieving optimal compression with respect to resource constraints is a difficult problem. For instance, in lossless

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Database Design with Genetic Algorithmsd the system load is equitably distributed among all locations. This problem is called the File Design Problem. This problem is NP Hard and requires the optimization over conflicting objectives. A genetic algorithm based on multi niche crowding combines heuristics with parallel processing to provide

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Designing Multiprocessor Scheduling Algorithms Using a Distributed Genetic Algorithm Systemiments. These approaches are usually quite time-consuming and produce only satisfactory solutions. To automate this process, we utilize current techniques in distributed computing, multithreading, and parallel processing to develop a distributed genetic algorithm system that designs new processor sc

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Prototyping Intelligent Vehicle Modules Using Evolutionary Algorithmshighlevel task goals with low-level sensor constraints to control simulated and (ultimately) real vehicles like the Carnegie Mellon Navlab robot vans..SAPIENT consists of a number of reasoning modules whose outputs are cornbined using a voting scheme. The behavior of these modules is directly depend

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Physical Design of VLSI Circuits and the Application of Genetic Algorithms today’s sub-micron regimes requiring new physical design algorithms. Genetic algorithms have been increasingly successful when applied in VLSI physical design in the last 10 years. Genetic algorithms for VLSI physical design are reviewed in general. In addition, a specific parallel genetic algorith