طراحی یک مدل ترکیبی جدید مبتنی بر تحلیل پوششی داده‌ها، شبکه عصبی مصنوعی، الگوریتم ژنتیک و بهینه‌سازی انبوه ذرات برای ارزیابی کارایی و الگوسازی واحد‌های کارا و ناکارا

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، واحد تهران مرکز، دانشگاه آزاد اسلامی.

2 دانشیار، واحد تهران مرکز، دانشگاه آزاد اسلامی.

3 استاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی.

10.29252/jimp.9.2.107

چکیده

هدف اصلی پژوهش حاضر، طراحی یک مدل ترکیبی جدید مبتنی بر تحلیل پوششی داده­‌ها، شبکه عصبی مصنوعی، الگوریتم ژنتیک و بهینه‌سازی انبوه ذرات برای ارزیابی کارایی و الگوسازی واحد­های کارا و نا­کارا است که واحد­های تصمیم­‌گیری در آن اندک باشد. فرایندی دومرحله­‌ای، برای ارزیابی کارایی نسبی۱۶ شرکت‌های برق منطقه‌ای شرکت توانیر، از مدل ترکیبی تحلیل پوششی داده‌ها با شبکه عصبی که به‌وسیله الگوریتم ژنتیک بهینه شده است، بهره برده است وبا یک الگوریتم ترکیبی انبوه ذرات با الگوریتم ژنتیک به الگوسازی برای واحدهای کارا و ناکارا پرداخته شده است. میانگین کارائی شرکت‌های برق منطقه­‌ای طی سال‌های ۱۳۹۱ تا ۱۳۹۶ از ۰/۸۹۳۴ به ۰/۹۱۴۷ افزایش یافته است و شرکت‌های برق منطقه‌­ای آذربایجان، اصفهان، تهران، خراسان، سمنان، کرمان، گیلان و یزد، همواره دارای بیشترین میانگین کارائی، ۱ و شرکت­‌های برق منطقه‌ای غرب و فارس با مقادیر میانگین کارائی  ۰/۷۰۴۷ و ۰/۶۰۲۵ دارای کمترین مقدار کارائی طی سال‌های ۱۳۹۱ تا ۱۳۹۶ بوده‌اند. 

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