最佳化的需求在我們日常生活中俯拾皆是。如何在有限的資源跟投資下,求得最大的經濟回收效益,是許多的企業終極的理想。雖然有許多演算法可以求得最佳化的可行解,然而不同演算法有不同的優缺點。本研究除了探討這些演算法的原理跟分析其優缺點外,又利用改良式基因演算法整合不同的方法的優缺點,以期達到效率及準確兼顧的最佳化工具。
The requirements of the optimization have filled within our daily life. The most common example is that many of the businesses pursuit high economic incomes with limited resources and investments. Although many available algorithms can help to produce feasible optimal solutions, yet trade-off and side-effect issues existed among these available algorithms. This study aims to the analysis of the merits of the individual algorithms, also utilizing the memetic approach to compensate the methods’ detriments. It is the goal of this study to obtain the memetic algorithm which equips efficiency and accuracy.