Genetic algorithms have proven to be a well-suited technique for solving selected combinatorial optimization problems. When solving real-world problems, often the main task is to find a proper representation for the candidate solutions. Strings of elementary data types with standard genetic operators may tend to create infeasible individuals during the search because of the discrete and often constrained search space. This article introduces a generally applicable representation for two-dimensional combinatorial placement and packing problems. Empirical results are presented for two constrained placement problems, the facility layout problem and the generation of very large scale integrated (VLSI) macro-cell layouts. For multiobjective optimization problems, common approaches often deal with the different objectives in different phases and thus are unable to efficiently solve the global problem. Due to a tree-structured genotype representation and hybrid, problem-specific operators, the proposed approach is able to deal with different constraints and objectives in one optimization step.
Lecture recordings can be a powerful addition to traditional lectures and they can even serve as a main content source in a number of didactic scenarios. If users can quickly locate relevant passages in a recording, the recording combines the ease of search that comes with electronic text based media with the authenticity and wealth of information that is delivered in a live lecture. Locating relevant passages in a time based media such as a recorded lecture is, however, not as easy as searching an electronic text document. This article presents the virtPresenter lecture recording system that tackles navigation in web lectures with a hypermedia navigation concept that is improved with interactive content overviews. Apart from navigation in web lectures the article also addresses didactic scenarios for web lectures and issues related to the workflow of recording lectures.
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