Dynamically and partially reconfigurable field-programmable gate arrays (FPGAs) allow to swap in and out tasks without interrupting the execution of other tasks. The FPGA controller can decide on-line where to place new tasks onto the FPGA. Rearranging a subset of the tasks executing on the FPGA may
Evolutionary approaches to solve three challenging engineering tasks
✍ Scribed by Martin Schütz; Hans-Paul Schwefel
- Book ID
- 104268340
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 1005 KB
- Volume
- 186
- Category
- Article
- ISSN
- 0045-7825
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✦ Synopsis
Three applications of evolutionary algorithms, namely the optimization of the nuclear core reload design, the synthesis of multilayer optical coatings, and the synthesis of chemical engineering plants, are presented in this paper. The examples demonstrate the applicability of the evolutionary approach to solve complex real-world problems. These problems are often mixed-integer, variabledimensional and multi-criteria optimization problems. Additionally, instead of an objective function, given in a closed form, complex simulation models are used as an objective function, thus prohibiting success by means of classical analysis.
Although standard evolutionary algorithms are not able to solve the three complex tasks presented here, enhanced evolutionary algorithms (EAs) clearly demonstrate their potential to do so. Through the three examples, we show the necessary ingredients for tackling real-world optimization problems. In addition to adequate representations and appropriate evolutionary operators, one needs to integrate expert knowledge and heuristic operators to guide the search. Finally, parallel EAs are needed to improve the reliability and speed up of evolutionary algorithms.
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