A Similarity-based Cellular Selection Mechanisim for Genetic algorithms to Solve Assignment Problems
نویسندگان
چکیده
In this paper, we illustrate a cellular structure mixed with Genetic Algorithms for solving assignment problems which have more than one feasible or optimum solution. Considering similarity among individuals in population, we use two dimensions Cellular Automata in order to place the individuals onto its cells to make the locality and neighborhood on Hamming distance basis. This new structure and using Genetic Algorithm on it, as 2D Cellular Automata Hamming GA, introduces locality for genetic selection and local knowledge for their selection process on cells of 2D Cellular Automata. The cellular selection based on the structure can ensure maintaining population diversity and fast convergence in the genetic search and improve the convergence performance during the genetic search. Keywords-Genetic Algorithms; Assignment Problems; Cellular Automata; Optimization; NP-hard Multi Solutions Problems
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