REX/JGG Algorithm

•

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makuramoto

Figure of REX/JGG Algorithm

Données & analyses

遺伝的アルゴリズム
(REX/JGG)
の流れ
株式会社Gunosy
ルクラ事業部
shunk (makuramoto1)

最適解
𝑓(𝑥)
前提：
凸関数𝑓(𝑥)があります．緑色が濃いほど𝑓(𝑥)が小さくなります．

最適解
初期動作：
𝑥の定義域内に，個体𝑥をランダムに𝑛個生成します．この𝑛
個の個体を集団𝑃とします
𝑥

最適解
𝑦1
𝑦2
𝑦3
アルゴリズム1：
集団𝑃からランダムに個体𝑦をμ個，非復元抽出する．この
抽出した個体を親個体とする

最適解
𝑦1
𝑦2
𝑦3
𝑥𝑖
アルゴリズム2：
親個体𝑦から個体𝑥𝑖を𝜆個生成する

最適解
𝑦1
𝑦2
𝑦3
𝑥𝑖
アルゴリズム3：
𝜆個生成された子個体𝑥𝑖を性能𝐶(𝑥𝑖)によって評価する．評価
が良い個体からμ個，個体を選択肢，集団𝑃に追加する．選
択されなかった子個体は集団に加えず，破棄する

最適解
𝑥𝑖
アルゴリズム3：
𝜆個生成された子個体𝑥𝑖を性能𝐶(𝑥𝑖)によって評価する．評価
が良い個体からμ個，個体を選択肢，集団𝑃に追加する．選
択されなかった子個体は集団に加えず，破棄する

最適解
アルゴリズム4:
アルゴリズム1~3を任意の回数繰り返し，評価値
が最も良い個体を最良個体𝑥 𝑏𝑒𝑠𝑡とする

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