الگوریتم های تکاملی تعاملی با اولویت تصمیم گیرندگان برای حل مسائل بهینه سازی چند هدفه بازه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|78936||2014||11 صفحه PDF||سفارش دهید||10237 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Neurocomputing, Volume 137, 5 August 2014, Pages 241–251
Interval multi-objective optimization problems (IMOPs), whose parameters are intervals, are considerably ubiquitous in real-world applications. Previous evolutionary algorithms (EAs) aim at finding the well-converged and evenly-distributed Pareto front. An EA incorporating with a decision-maker (DM)׳s preferences was presented in this study to obtain a Pareto-optimal subset that meets the DM׳s preferences. In this algorithm, the DM׳s preferences in terms of the relative importance of objectives were interactively input, and the corresponding preferred regions were then obtained. Based on these regions, solutions with the same rank were further distinguished to guide the search towards the DM׳s preferred region. The proposed method was empirically evaluated on four IMOPs and compared with other state-of-the-art methods. The experimental results demonstrated the simplicity and the effectiveness of the proposed method.