書誌事項
- タイトル別名
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- 2208 Functional Characteristics of the Search-Space Smoothing Method in Combination with the Metropolis Algorithm I
- メトロポリスアルゴリズムとの併用による探索空間平滑化法の機能特性(2)
- メトロポリスアルゴリズム ト ノ ヘイヨウ ニ ヨル タンサク クウカン ヘイカツカホウ ノ キノウ トクセイ(2)
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The optimization function of the method of search-space smoothing (SSS) in combination with the Metropolis algorithm (MA) is studied on the random Euclidean traveling salesman problem. The search dynamics of this combined approach (MASSS) are analyzed in both the smoothed and unsmoothed terrains and compared to those of the original SSS method. The results show that the MA can be successfully utilized as a local search algorithm in the SSS approach and the optimization characteristics of these two constituent methods are improved in a mutually beneficial manner in the MASSS run: The relaxation dynamics generated by employing the MA effectively work even in a smoothed terrain and more advantage is taken of the guiding function proposed in the idea of SSS. Also, this mechanism operates in an adaptive manner in the de-smoothing process and the MASSS method maintains its performance over a wider temperature range than does the MA.
収録刊行物
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- 最適化シンポジウム：OPTIS
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最適化シンポジウム：OPTIS 2012.10 (0), _2208-1_-_2208-6_, 2012
一般社団法人 日本機械学会