貪婪算法

• 每步均選擇局部的最優解，重復此過程，最終即得到全局的最優解
• 簡而言之就是每步都采用最優解

優點：

• 簡單易行

缺點：

• 并非在所有情況下都奏效

經典的問題：

背包問題

集合覆蓋問題

貪婪算法下的近似算法解決集合覆蓋問題

states_needed = set(["mt", "wa", "or", "id", "nv", "ut", "ca", "az"])stations = {} stations["kone"] = set(["id", "nv", "ut"]) stations["ktwo"] = set(["wa", "id", "mt"]) stations["kthree"] = set(["or", "nv", "ca"]) stations["kfour"] = set(["nv", "ut"]) stations["kfive"] = set(["ca", "az"]) final_stations = set()while states_needed:best_station = Nonestates_covered = set()for station, states in stations.items():covered = states_needed & statesif len(covered) > len(states_covered):best_station = stationstates_covered = coveredstates_needed -= states_coveredfinal_stations.add(best_station)print(final_stations)

轉載于:https://www.cnblogs.com/huang-yc/p/10322363.html

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