[صفحه اصلی ]   [Archive]  
:: صفحه اصلي :: درباره نشريه :: آخرين شماره :: تمام شماره‌ها :: جستجو :: ثبت نام :: ارسال مقاله :: تماس با ما ::
بخش‌های اصلی
صفحه اصلی::
اطلاعات نشریه::
آرشیو مجله و مقالات::
ارسال مقاله::
برای داوران::
ثبت نام و اشتراک::
تماس با ما::
تسهیلات پایگاه::
سایتهای مرتبط::
صورتجلسات::
نشانی::
::
جستجو در پایگاه

جستجوی پیشرفته
دریافت اطلاعات پایگاه
نشانی پست الکترونیک خود را برای دریافت اطلاعات و اخبار پایگاه، در کادر زیر وارد کنید.
آخرین مطالب بخش
:: راه‌اندازی پایگاه
:: جلد 8، شماره 2 - ( 2-1396 ) ::
جلد 8 شماره 2 صفحات 47-40 برگشت به فهرست نسخه ها
A Dual Active-Set Algorithm for Regularized Slope-Constrained Monotonic Regression
چکیده:   (9389 مشاهده)
In many problems, it is necessary to take into account monotonic relations. Monotonic (isotonic) Regression (MR) is often involved in solving such problems. The MR solutions are of a step-shaped form with a typical sharp change of values between adjacent steps. This, in some applications, is regarded as a disadvantage. We recently introduced a Smoothed MR (SMR) problem which is obtained from the MR by adding a regularization penalty term. The SMR is aimed at smoothing the aforementioned sharp change. Moreover, its solution has a far less pronounced step-structure, if at all available. The purpose of this paper is to further improve the SMR solution by getting rid of such a structure. This is achieved by introducing a lowed bound on the slope in the SMR. We call it Smoothed Slope-Constrained MR (SSCMR) problem. It is shown here how to reduce it to the SMR which is a convex quadratic optimization problem. The Smoothed Pool Adjacent Violators (SPAV) algorithm developed in our recent publications for solving the SMR problem is adapted here to solving the SSCMR problem. This algorithm belongs to the class of dual active-set algorithms. Although the complexity of the SPAV algorithm is $𝑂(𝑛^2)$, its running time is growing in our computational experiments almost linearly with $𝑛$. We present numerical results which illustrate the predictive performance quality of our approach. They also show that the SSCMR solution is free of the undesirable features of the MR and SMR solutions.
متن کامل [PDF 545 kb]   (14934 دریافت)    
نوع مطالعه: پژوهشی | موضوع مقاله: Other
دریافت: 1397/3/7 | پذیرش: 1397/3/7 | انتشار: 1397/3/7
ارسال نظر درباره این مقاله
نام کاربری یا پست الکترونیک شما:

CAPTCHA



XML   English Abstract   Print



بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.
جلد 8، شماره 2 - ( 2-1396 ) برگشت به فهرست نسخه ها
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
Persian site map - English site map - Created in 0.11 seconds with 38 queries by YEKTAWEB 4645