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مقایسه قابلیت الگوریتم جهش تصادفی قورباغه با دیگر الگوریتم‌های فراکاوشی در طراحی شبکه‌های فاضلاب شهری | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 17، دوره 54، شماره 6، شهریور 1401، صفحه 2375-2394 اصل مقاله (2.25 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2021.19609.7215 | ||
| نویسندگان | ||
| فریبرز معصومی* 1؛ سینا معصوم زاده2؛ نگین ظفری3؛ سارا اسفندمز3 | ||
| 1دانشگاه محقق اردبیلی، اردبیل، ایران | ||
| 2دانشکده مهندسی عمران دانشگاه تبریز | ||
| 3دانشگاه محقق اردبیلی | ||
| چکیده | ||
| بهینه سازی طراحی شبکه های جمع آوری و انتقال فاضلاب شهری به دلیل هزینه های بسیار بالای اجرای این زیرساخت ها همواره مورد توجه محققین و کارشناسان بوده است. تعدد متغیرهای تصمیم و پیچیده بودن قیودات حاکم بر مسئله، استفاده از روش‌های ریاضیاتی را در بهینه سازی این سیستمها با دشواری های زیادی همراه کرده و این امر استفاده از الگوریتم های فراکاوشی را در حل این مسائل ضروری ساخته است. الگوریتم جهش تصادفی قورباغه یکی از الگوریتم های فراکاوشی جدید است که قابلیت خود را در حل تعداد زیادی از مسائل بهینه سازی نشان داده است. در این تحقیق، قابلیت الگوریتم جهش تصادفی قورباغه در حل مسئله طراحی بهینه شبکه های فاضلاب شهری مورد بررسی قرار گرفته است. قطر لوله ها به عنوان متغیرهای تصمیم گسسته و عمق کارگذاری لوله ها به عنوان متغیرهای تصمیم پیوسته، همزمان در این تحقیق به عنوان مجهولات مسئله مطرح بوده اند. همچنین سه شبکه فاضلاب با 13، 41 و 65 متغیر تصمیم (به صورت ترکیبی از تعداد لوله‌ها و تعداد گره‌ها) به عنوان مطالعه موردی انتخاب شده است. رعایت قیودات متعدد فنی، اجرایی و هیدرولیکی نیز با تعریف توابع جریمه مناسب کنترل شده است. نتایج نشان داد که نتایج به دست آمده از الگوریتم جهش تصادفی قورباغه در مقایسه با بهترین پاسخ به دست آمده از الگوریتم‌های ژنتیک، هوش تجمعی ذرات و رقابت زیست طبیعی در مسائل اول و سوم به ترتیب منجر به کاهش هزینه به میزان 0/43 و 3/2 درصد شده و در مسئله دوم نیز در مقایسه با دیگر روش‌ها، با کمترین میزان تعداد فراخوانی تابع هدف به تابع هدفی برابر دست یافته است. | ||
| کلیدواژه‌ها | ||
| الگوریتم فراکاوشی؛ بهینه‌سازی؛ حداقل‌سازی هزینه؛ شبکه فاضلاب شهری؛ الگوریتم جهش تصادفی قورباغه | ||
| موضوعات | ||
| مهندسی آب و فاضلاب | ||
| عنوان مقاله [English] | ||
| Comparison of the Capability of Shuffled Frog Leaping Algorithm with Other Metaheuristic Algorithms in Design of Urban Sewage Network | ||
| نویسندگان [English] | ||
| fariborz masoumi1؛ sina masoumzadeh2؛ Negin Zafari3؛ saea esfandmaz3 | ||
| 1Department of civil engineering, faculty of engineering, university of mohaghegh ardabili, Ardabil, Iran | ||
| 2Civil Engineering faculty, Tabriz University | ||
| 3Mohaghegh Ardabili University | ||
| چکیده [English] | ||
| The optimal design and construction of sewage networks have always been considered by researchers and experts due to the very high costs of implementing this infrastructure. Being consisted of various variables and subjected to complex constraints, conventional mathematical optimization procedures are unlikely to be able to solve sewage network optimization problems. Thus, utilizing meta-heuristic optimization algorithms is a must to tackle these problems. The shuffled frog leaping algorithm (SFLA) is one of the new meta-heuristic algorithms which has shown its ability to solve a large number of optimization problems. In this research, the capability of the SFLA in solving the problem of optimal design of sewage networks has been investigated. The diameter of the pipes as discrete decision variables and the depth of pipe placement as continuous decision variables were simultaneously considered in this study as unknowns. To this end, three sewage networks with 13, 41, and 65 decision variables have been selected as case studies. Various technical, operational, and hydraulic constraints are controlled by defining appropriate penalty functions. The results showed that for case studies 1 and 3, the SFLA decreased the minimum construction costs derived by GA, PSO, and SCE algorithms by 0.43 and 3.2 percent respectively, and for the second case study, with the less number of function evaluations, SFLA has reached the equal objective function compared to other algorithms. | ||
| کلیدواژه‌ها [English] | ||
| Metaheuristic algorithm, Optimization, Cost minimization, Urban Sewage Networks, Shuffled frog leaping algorithm | ||
| مراجع | ||
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