A Focus and Constraint based Genetic Algorithm for Interactive Directed Graph Drawing
作者： Peter Eades , Hugo A. D. do Nascimento
DOI:
关键词: Convergence (routing) 、 Constraint (information theory) 、 Domain knowledge 、 Artificial intelligence 、 Directed graph 、 Machine learning 、 Genetic algorithm 、 Focus (computing) 、 Representation (mathematics) 、 Computer science
摘要: This paper presents a user-driven genetic algorithm for directed graph drawing. An interactive framework is considered where users can focus the on regions of drawing that need major improvement, or include domain knowledge as layout constraints. The describes how and user constraints are managed by algorithm. combination user’s skills with automatic tools allows more flexible efficient optimization method, when compared to traditional non-interactive algorithms. Issues regarding memory usage, processing time, solution representation convergence discussed here.
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