منابع مشابه
Interactive multi - objective optimization for simulated moving bed processes
In this paper, efficient optimization techniques are used to solve multi-objective optimization problems arising from Simulated Moving Bed (SMB) processes. SMBs are widely used in many industrial separations of chemical products and they are very challenging from the optimization point of view. With the help of interactive multi-objective optimization, several conflicting objectives can be cons...
متن کاملsolution of security constrained unit commitment problem by a new multi-objective optimization method
چکیده-پخش بار بهینه به عنوان یکی از ابزار زیر بنایی برای تحلیل سیستم های قدرت پیچیده ،برای مدت طولانی مورد بررسی قرار گرفته است.پخش بار بهینه توابع هدف یک سیستم قدرت از جمله تابع هزینه سوخت ،آلودگی ،تلفات را بهینه می کند،و هم زمان قیود سیستم قدرت را نیز برآورده می کند.در کلی ترین حالتopf یک مساله بهینه سازی غیر خطی ،غیر محدب،مقیاس بزرگ،و ایستا می باشد که می تواند شامل متغیرهای کنترلی پیوسته و گ...
Directed Multi-Objective Optimization
While evolutionary computing inspired approaches to multi-objective optimization have many advantages over conventional approaches; they generally do not explicitly exploit directional/gradient information. This can be inefficient if the underlying objectives are reasonably smooth, and this may limit the application of such approaches to real-world problems. This paper develops a local framewor...
متن کاملmulti-objective optimization of hydropwoer multi-objective optimization of hydropower reservoirs operation based on the pattern of PAB markets
In recent years, the structure of the electricity industry has undergone a change and since November 2003, when the electricity market of the country was launched, its monopoly structure has become a competitive structure. In this market, the forecast of electricity prices is not only necessary in pricing but also plays an important role in finding the optimal operation strategy by the power pl...
متن کاملBayesian Optimization Algorithms for Multi-objective Optimization
In recent years, several researchers have concentrated on using probabilistic models in evolutionary algorithms. These Estimation Distribution Algorithms (EDA) incorporate methods for automated learning of correlations between variables of the encoded solutions. The process of sampling new individuals from a probabilistic model respects these mutual dependencies such that disruption of importan...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Aeronautics and Aerospace Open Access Journal
سال: 2019
ISSN: 2576-4500
DOI: 10.15406/aaoaj.2019.03.00076