ارائه مدلی جهت مدیریت مصارف آبی کشاورزی، صنعتی و خانگی ایران با ترکیب پویایی‌شناسی سیستم‌ها و الگوریتم ژنتیک

فصلنامه علمی مهندسی منابع آب

مقاله 5، دوره 17، شماره 63، اسفند 1403، صفحه 65-81   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.30495/wej.2024.32541.2398

نویسندگان

مریم موثقی گیلانی¹؛ محمد علی افشار کاظمی^{* 2}؛ محمد علی کرامتی²

¹دانشجوی دکتری مدیریت صنعتی، دانشکده مدیریت، دانشگاه آزاد اسلامی تهران مرکز

²دانشیار، دانشکده مدیریت، دانشگاه آزاد اسلامی تهران مرکز

تاریخ دریافت: 16 مهر 1402،  تاریخ بازنگری: 28 آذر 1402،  تاریخ پذیرش: 25 بهمن 1402 

چکیده

مقدمه: در این تحقیق سیستم مدیریت منابع آبی کشور با رویکرد پویایی‌شناسی سیستم‌ها مدل سازی شده و پس از شبیه‌سازی به تعیین میزان بهینه منابع آبی، قدرت اجتماعی حاکمیت، منابع مالی دولت و میزان مهاجرت‌های آبی با توجه به متغیرهای تصمیم تعرفه آب خانگی، کشاورزی و صنعتی پرداخته شده است. نتایج ترکیب بهینه، افزایش تعرفه آب در بخش خانگی، کشاورزی و صنعتی جهت بهینه‌سازی تابع هدف را به ترتیب 11، 200 و 200 درصد در طی 5 سال آینده پیشنهاد می‌نماید.
روش­: این تحقیق در ابتدا با استفاده از ابزار پویایی‌شناسی سیستم‌ها متغیرها و حلقه‎های بازخوری دخیل در مدیریت منابع آبی را مدلسازی و شبیه‌سازی کرده است. به‌منظور بهینه‌سازی از دو روش الگوریتم ژنتیک و قابلیت Simulation-optimization در نرم‌افزار ونسیم استفاده شده است. در الگوریتم ژنتیک جمعیت اولیه 30 عدد و احتمال تقاطع و جهش به ترتیب 83 درصد و 17 درصد جمعیت در نظر گرفته شده است. معیار انتخاب هر کروموزوم با روش roulet wheel می‌باشد.
یافته ­ها: نتایج نشان داد بهینه‌سازی با الگورتیم ژنتیک نسبت به ادامه شرایط پایه، منابع آبی پشت سدها را 89 درصد افزایش داده در صورتی که خروجی نرم‌افزار ونسیم 84 درصد بهبود می‌دهد و در کل خروجی الگورتیم ژنتیک نسبت به خروجی بهینه‌سازی نرم‌افزار ونسیم، تابع هدف را 2 درصد بالاتر بهبود می‌دهد.
نتیجه­ گیری: نتایج نشان داد بهینه‌سازی با الگوریتم ژنتیک در قیاس با نرم‌افزار ونسیم نتایج قابل قبول‌تری ارائه می‌دهد. همچنین پس از بهینه‌سازی، بهترین سیاست تعرفه‌ای جهت بهبود تابع هدف افزایش بیشتر در تعرفه آب کشاورزی و صنعتی نسبت به تعرفه خانگی است.

کلیدواژه‌ها

مدیریت منابع آبی؛ پویایی‌شناسی سیستم‌ها؛ الگوریتم ژنتیک

عنوان مقاله [English]

Presenting A Model for Managing Agricultural, Industrial, And Household Water Consumption in Iran by Combining System Dynamics and Genetic Algorithm

نویسندگان [English]

Maryam Movaseghi Gilani¹؛ Mohamad Ali Afshar Kazemi²؛ Mohamad Ali Keramati²

¹Ph. D. Candidate of Industrial Management, Management Faculty, Islamic Azad University South Tehran Branch, Tehran, Iran

²Associate professor, Information Technology and Industrial Management, Management Faculty, Islamic Azad University Central Tehran Branch, Tehran, Iran

چکیده [English]

Introduction: In this study, the country's water resources management system has been modeled using a system dynamics approach. After simulation, optimal water resources, social power of governance, government financial resources, and the rate of water migration have been determined based on the decision variables of household, agricultural, and industrial water tariffs. The optimal combined results suggest an 11%, 200%, and 200% increase in water tariffs for household, agricultural, and industrial sectors, respectively, over the next 5 years.
Methods: Initially, this study modeled and simulated the variables and feedback loops involved in water resources management using system dynamics tools. For optimization, two methods, genetic algorithm and the Simulation-optimization capability in the Vensim software, were employed. In the genetic algorithm, an initial population of 30 individuals and crossover and mutation probabilities of 83% and 17% were considered. The selection criterion for each chromosome is based on the roulette wheel method.
Findings: The results indicate that optimization using the genetic algorithm results in an 89% increase in water resources behind dams compared to the baseline conditions, whereas the Vensim software output shows an 84% improvement. Overall, the genetic algorithm improves the objective function by 2% compared to the Vensim software's optimization output. Additionally, after optimization, the best tariff policy for enhancing the objective function is a further increase in agricultural and industrial water tariffs compared to household tariffs.

کلیدواژه‌ها [English]

Water resource management, System dynamics, Genetic algorithm

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