دانلود مقاله ISI انگلیسی شماره 49498
عنوان فارسی مقاله

طراحی مرکز کنترل مدیریت منابع آب SCADA با یک مشکل تخصیص افزونگی دو هدفه و بهینه سازی ازدحام ذرات

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
49498 2015 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Design of SCADA water resource management control center by a bi-objective redundancy allocation problem and particle swarm optimization
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Reliability Engineering & System Safety, Volume 133, January 2015, Pages 11–21

کلمات کلیدی
SCADA - مشکل تخصیص افزونگی چند هدفه - متا اکتشافی - بهینه سازی ازدحام ذرات چند هدفه - روش ε محدودیت - شبکه تطبیقی
پیش نمایش مقاله
پیش نمایش مقاله طراحی مرکز کنترل مدیریت منابع آب SCADA با یک مشکل تخصیص افزونگی دو هدفه و بهینه سازی ازدحام ذرات

چکیده انگلیسی

SCADA1 is an essential system to control critical facilities in big cities. SCADA is utilized in several sectors such as water resource management, power plants, electricity distribution centers, traffic control centers, and gas deputy. The failure of SCADA results in crisis. Hence, the design of SCADA system in order to serve a high reliability considering limited budget and other constraints is essential. In this paper, a bi-objective redundancy allocation problem (RAP) is proposed to design Tehran׳s SCADA water resource management control center. Reliability maximization and cost minimization are concurrently considered. Since the proposed RAP is a non-linear multi-objective mathematical programming so the exact methods cannot efficiently handle it. A multi-objective particle swarm optimization (MOPSO) algorithm is designed to solve it. Several features such as dynamic parameter tuning, efficient constraint handling and Pareto gridding are inserted in proposed MOPSO. The results of proposed MOPSO are compared with an efficient ε-constraint method. Several non-dominated designs of SCADA system are generated using both methods. Comparison metrics based on accuracy and diversity of Pareto front are calculated for both methods. The proposed MOPSO algorithm reports better performance. Finally, in order to choose the practical design, the TOPSIS algorithm is used to prune the Pareto front.

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