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Learning and re-using information in space layout planning problems using genetic engineering
Affiliation:1. Tsinghua University;2. Beijing Institute of Technology;3. Tsinghua University;1. Alliance Manchester Business School, University of Manchester, Manchester M13 9SS, United Kingdom;2. Department of Enterprise Engineering, University of Rome “Tor Vergata”, 00133 Rome, Italy;3. Lancaster University Management School, Lancaster University, Bailrigg, Lancaster LA1 4YX, United Kingdom;1. Computer Science Department, University of California, Los Angeles, USA;2. Computer and Information Science Department, University of Pennsylvania, USA
Abstract:We describe the use of a genetic engineering version of genetic algorithms as a natural tool for gathering and re-using information about some classes of design problems. This information is stored in the form of sets of ‘evolved genes’ which are linked to beneficial qualities of the ‘good’ designs within this class of problems. The approach is illustrated on a space layout planning problem.
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