الگوریتم ژنتیک مبتنی بر کد واقعی با جهش هوشمند برای حل مسائل پخش بار اقتصادی غیرمحدب

نویسندگان

دانشگاه تبریز

چکیده

در این مقاله، یک روش جدید برای حل مسائل پخش بار اقتصادی با استفاده از الگوریتم ژنتیک مبتنی بر کدهای واقعی با جهش هوشمند پیشنهاد می شود. در روش پیشنهادی کنترل لازم بر روی مقادیر مجموع کروموزوم ها صورت می‌گیرد در نتیجه نیازی به استفاده از هزینه جریمه در حل مسئله پخش بار اقتصادی نخواهد بود. این روش بر روی الگوریتم ژنتیک کلاسیک جهت حل مسائل پخش بار اقتصادی غیر محدب پیاده شده است .روش پیشنهادی قابلیت تعمیم و پیاده سازی بر روی انواع مسایل بهینه‌سازی را دارد. روش پیشنهادی ضمن کاهش محدوده جستجو، تنها در محدوده منطقی و قابل قبول شروع به اکتشاف هزینه بهینه می‌نماید. برای نشان دادن کارایی و عملکرد روش پیشنهادی، حل مسئله پخش بار اقتصادی با انواع قیودها در سیستم‌های 6 ژنراتوره، 15 ژنراتوره و 40 ژنراتوره با استفاده از روش پیشنهادی صورت گرفته است. نتایج کار با نتایج سایر الگوریتم‌های پیشرفته‌ تکنیکی مقایسه شده است که نشان دهنده برتری روش پیشنهادی نسبت به سایر روش‌ها می‌باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Real-Coded Genetic Algorithm with Smart Mutation for Solving Nonconvex Economic Dispatch Problems

نویسندگان [English]

  • Naser Ghorbani
  • Ebrahim Babaei
University of Tabriz
چکیده [English]

In this paper, real-coded genetic algorithm with smart mutation (RCGA-SM) is proposed to solve the economic dispatch (ED) problem. In the proposed method, the required controlling process is accomplished on the total amount of chromosomes and consequently there is no need to use penalty cost function for controlling sum of variables in solving economic dispatch problem. This method will begin to explore the optimal answer just within the logic and acceptable zone in addition to its capability in reducing the search range. In order to show the performance and the efficiency of the proposed method, the ED problem considering several constraints is solved in 6, 15, and 40 units systems through the proposed technique. The proposed coding could effectively escapes from infeasible solutions. Thereby search efficiency and solution quality are dramatically improved. The obtained results are compared with other advanced technical algorithms, which well depicts the superiority of the RCGA-SM technique over the others compared methods.

کلیدواژه‌ها [English]

  • Economic Dispatch
  • nonconvex optimization
  • penalty function
  • smart mutation

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