A new self scaling PCG algorithm with dynamical retards

Abstract

‫ايج‬ ‫مسالة‬ ‫ان‬ ‫االمث‬ ‫الحل‬ ‫اد‬ ‫ل‬ ‫تعظيم‬ ‫دالة‬ ‫بشكل‬ ‫صياغتها‬ ‫يمكن‬ ‫لمزمن‬ ‫كدالة‬ ‫معين‬ ‫لنظام‬ ‫لدالة‬ ‫تصغير‬ ‫او‬ ‫الكمفة‬ ‫غير‬ ‫ال‬ ‫خطية‬ . ‫الديناميكية‬ ‫البرمجة‬ ‫ارزميات‬ ‫خو‬ ‫أن‬ ‫خاص‬ ‫بشكل‬ ‫وجد‬ ‫وقد‬ ‫الخطية‬ ‫غير‬ ‫ية‬ ‫ار‬ ‫التكر‬ ‫البرمجة‬ ‫طرق‬ ‫الت‬ ‫محاو‬ ‫مع‬ ‫نة‬ ‫مقار‬ ‫المسائل‬ ‫هذه‬ ‫لحل‬ ‫كفوءة‬ . ‫هذا‬ ‫عممنا‬ ‫وفي‬ , ‫االنح‬ ‫طرق‬ ‫عممت‬ ‫ديناميكية‬ ‫يقة‬ ‫بطر‬ ‫ورففت‬ ‫الديناميكية‬ ‫االعاقة‬ ‫مع‬ ‫المتدرج‬ ‫دار‬ ‫ال‬ ‫لمدو‬ ‫التصغير‬ ‫ارزميات‬ ‫خو‬ ‫من‬ ‫جديد‬ ‫نوع‬ ‫عمى‬ ‫لمحصول‬ ‫تيبة‬ ‫الر‬ ‫غير‬ ‫اتيجيات‬ ‫االستر‬ ‫مع‬ ‫االمثمية‬ ‫في‬ ‫الالخطية‬ ‫المسائل‬ ‫مع‬ ‫بكفاءة‬ ‫تتعامل‬ ‫التي‬ ‫بيعية‬ ‫التر‬ ‫غير‬ ‫العالي‬ ‫القياس‬ ‫ذات‬ . AbstractThe problem of optimizing a certain systems as a function of time may be formulated in terms of maximizing or minimizing a non-linear cost function. It was found that a Dynamic Programming (DP) algorithm was particularly efficient procedure for solving this problem compared with an alternative nonlinear programming method. In this work, a new CG method with dynamical retards is generalized and combined in a dynamical way with non-monotone globalization strategies to obtain a new type CG-algorithm for minimizing non-quadratic functions that can deal efficiently with large scale nonlinear optimization problems.