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详细说明： This is a GA implementation for multi-objective optimization. *** *** For multi-objective optimization, non-domonated sorting has *** *** been used. The design variables can be Binary, Integer, Real *** *** or Enumerated data type. Moreover a design vector can have *** *** design variables where each variable can be any of the above *** *** mentioned types. The order in which the design variables *** *** are needed is also maintained in the code. For multi-objective*** *** optimization, sharing is done using e ither of two ways : *** *** Sharing on Fitness Space or Sharing on Parameter Space. After *** *** completion, results are stored in a 'result.out' and for *** *** detailed inspection in a file 'report'. For a detail discussion*** *** please refer to Journal paper: *** *** Srinivas, N. and Deb, K. (1994). Multiobjective optimization *** *** using nondominated sorting genetic algorithms. Evolutionary *** *** Computation. Vol. 2, No. 3. Pages 221--248. ...展开收缩
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