Current evolutionary multiobjective optimization (EMO) approaches tend to emphasize the approximation of the Pareto-optimal front as a whole, thereby dissociating the optimization process from the selection of the fin...
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In this paper, an better evolutionary algorithm based on decomposition and grid-based Pareto dominance (MOEA/DG) is proposed to work out many-objective optimization problems. The main goal is to heighten the convergen...
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Target shape design optimization problem is to approximate an unknown shape, when a black-box function provides the fitness of the shape. The framework to solve this problem can be applied to the finding of optimized ...
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The internal layouts of buildings in video games are usually designed by hand, but the increasingly expansive and realistic nature of virtual worlds introduces scalability issues which make manual design methods impra...
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ISBN:
(纸本)9783319135632;9783319135625
The internal layouts of buildings in video games are usually designed by hand, but the increasingly expansive and realistic nature of virtual worlds introduces scalability issues which make manual design methods impractical. We present a new methodology that uses a multiobjective evolutionary algorithm to automatically generate building layouts. The method accepts highly versatile input constraints, encoding layouts using a flexible binary tree representation and evaluating them on a range of criteria to ensure authentic results. Tests demonstrate that the method works well for a variety of problem instances representing an apartment, a family house, and an office floor;the ability to generate solutions for different types of buildings and to incorporate non-rectangular spaces shows greater versatility than many previous methods.
evolutionary algorithms (EAs) have been applied to various combinatorial optimization problems. Bacterial evolutionary algorithm (BEA) is an optimization method that incorporates special mechanisms inspired by natural...
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We introduce an evolutionary algorithm to solve the short-term electrical generation scheduling problem (STEGS). This algorithm is based on a new nonbinary coding scheme that reduces drastically the search space. We a...
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In feature selection we aim at reducing the dimensionality of a dataset by excluding characteristics that do not compromise, and potentially enhance, the classification of a set of samples. We present a new type of su...
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We describe a multi-objective evolutionary algorithm that designs multi-deviceWi-Fi installations optimised for three criteria: minimised cost, maximised coverage, and minimised service refusal. At the heart of the sy...
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ISBN:
(纸本)9783319135632;9783319135625
We describe a multi-objective evolutionary algorithm that designs multi-deviceWi-Fi installations optimised for three criteria: minimised cost, maximised coverage, and minimised service refusal. At the heart of the system is a detailed simulator for Wi-Fi installations, and a simple parallel evaluation scheme to allow these simulations to be performed in reasonable time. We show that the algorithm can derive good installations for two real-world maps requiring respectively around ten and fifty access points. The fine-grained connectivity and mobility models used in the simulator allow us to derive results that are more realistic than do previous methods.
This paper presents a method for the optimization of reference tracks which will be used as maps by an autonomous vehicle. Given a track obtained during a manual driving session by a GPS sensor installed in the vehicl...
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evolutionary testing is a very popular domain in the field of search based software engineering that consists in automatically generating test cases for a given piece of code using evolutionary algorithms. One of the ...
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evolutionary testing is a very popular domain in the field of search based software engineering that consists in automatically generating test cases for a given piece of code using evolutionary algorithms. One of the most important measures used to evaluate the quality of the generated test suites is code coverage. In this paper we want to analyze if there exists a correlation between some static measures computed on the test program and the code coverage when an evolutionary test case generator is used. In particular, we use evolutionary Strategies (ES) as search engine of the test case generator. We have also developed a program generator that is able to create Java programs with the desired values of the static measures. The experimental study includes a benchmark of 3600 programs automatically generated to find correlations between the measures. The results of this study can be used in future work for the development of a tool that decides the test case generation method according to the static measures computed on a given program.
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