Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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Abstract: Cellular automata are used to represent physical objects and their interactions for the purpose of planning the assembly process of several parts. Cells assume a vector value, made up of a material/void indicator, a set of cell boundary edge states, and an indicator of the allowable motion direction of the cell. Sets of rules that recognize parts and deduce allowable motions are described. An algorithm to generate allowable disassembly sequences is developed. An implementation is used to study the performance of the rules and algorithm. An example sequence generations is presented.