Abstract
The De-Novo programming problem proposed by Zeleny is well-known for its value on designing an optimal system by extending existed resources instead of finding the optimum in a given system with fixed resources. Since few papers are dedicated to explore the De-Novo programming problem with multiple stages and its resolution approach, the De-Novo programming problem is innovatively extended to a fuzzy dynamic programming problem in this paper, which is solved by the evolving algorithm so as to reflect greater realities. First, a traditional De-Novo programming problem is modified to a De-Novo programming problem with multiple fuzzy goals, fuzzy constraints and multiple stages. Second, we regard this fuzzy multi-stage De-Novo programming problem as a fuzzy dynamic programming problem, which is identical to a fuzzy multi-objective combinatorial optimization problem. Finally, we actually validate the feasibility of genetic algorithm on such a problem.
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