Evaluating the Effectiveness of Applying Genetic Algorithms for NVP System Design

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  • NVPシステム設計に対する遺伝的アルゴリズム適用の有効性の評価
  • NVP システム セッケイ ニ タイスル イデンテキ アルゴリズム テキヨウ ノ ユウコウセイ ノ ヒョウカ

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The N-version programming (NVP) approach is a kind of fault tolerant techniques and is a software system employing functionally equivalent, yet independently developed software components. It relies on the application of design diversity (i.e., program versions are independently designed to meet the same system requirements). A consistent set of inputs is supplied to all versions and all N versions are executed in parallel. A decision mechanism must gather the available results from N versions and determine the result to be delivered to the user. When constructing a large-size software system with extremely high reliability, we must use components with much higher reliability, however, this is very expensive. Therefore a large, highly reliable software system should be designed while minimizing cost. Genetic algorithms are known as one of the most powerful optimizers or near-optimizers of combinatorial optimization problems. We propose two genetic algorithms, one employing "random key representation", and the other employing "binary representation", for solving the N-version program design problem formulated as a 0-1 non-linear integer programming problem, respectively. Further, the efficiency of the proposed GAs is proven through some numerical experiments. Then, the characteristics of each representation scheme are investigated and evaluated.

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