Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

With the increasing scarcity of water resources, the growing importance of the optimization operation of the multireservoir system in water resources development, utilization, and management is increasingly evident. Some of the existing optimization methods are inadequate in applicability and effectiveness. Therefore, we need further research in how to enhance the applicability and effectiveness of the algorithm. On the basis of the research of the multireservoir system’s operating parameters in the Urumqi River basin, we establish a multiobjective optimization problem (MOP) model of water resources development, which meets the requirements of water resources development. In the mathematical model, the domestic water consumption is the biggest, the production of industry and agricultural is the largest, the gross output value of industry and agricultural is the highest, and the investment of the water development is the minimum. We use the weighted variable-step shuffled frog leaping algorithm (SFLA) to resolve it, which satisfies the constraints. Through establishing the test function and performance metrics, we deduce the evolutionary algorithms, which suit for solving MOP of the scheduling, and realize the multiobjective optimization of the multireservoir system. After that, using the fuzzy theory, we convert the competitive multiobjective function into single objective problem of maximum satisfaction, which is the only solution. A feasible solution is provided to resolve the multiobjective scheduling optimization of multireservoir system in the Urumqi River basin. It is the significance of the layout of production, the regional protection of ecological environment, and the sufficient and rational use of natural resources, in Urumqi and the surrounding areas

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

With the increasing scarcity of water resources, the growing importance of the optimization operation of the multireservoir system in water resources development, utilization, and management is increasingly evident. Some of the existing optimization methods are inadequate in applicability and effectiveness. Therefore, we need further research in how to enhance the applicability and effectiveness of the algorithm. On the basis of the research of the multireservoir system's operating parameters in the Urumqi River basin, we establish a multiobjective optimization problem (MOP) model of water resources development, which meets the requirements of water resources development. In the mathematical model, the domestic water consumption is the biggest, the production of industry and agricultural is the largest, the gross output value of industry and agricultural is the highest, and the investment of the water development is the minimum. We use the weighted variable-step shuffled frog leaping algorithm (SFLA) to resolve it, which satisfies the constraints. Through establishing the test function and performance metrics, we deduce the evolutionary algorithms, which suit for solving MOP of the scheduling, and realize the multiobjective optimization of the multireservoir system. After that, using the fuzzy theory, we convert the competitive multiobjective function into single objective problem of maximum satisfaction, which is the only solution. A feasible solution is provided to resolve the multiobjective scheduling optimization of multireservoir system in the Urumqi River basin. It is the significance of the layout of production, the regional protection of ecological environment, and the sufficient and rational use of natural resources, in Urumqi and the surrounding areas

Система аналізу та оптимізації транспортних пасажирських потоків

У даній роботі було поставлено завдання розробити алгоритм пошуку оптимального набору маршрутів громадського транспорту методами колективного інтелекту. Було проаналізовано існуючі критерії оптимізації та різні способи вирішення даної задачі. Громадський транспорт відноситься до числа найважливіших галузей життєзабезпечення міста, від функціонування яких залежать якість життя населення, ефективність роботи галузей економіки міста та можливість використання її містобудівного та соціально-економічного потенціалу. Проте зараз в Україні громадський транспорт є малорозвиненим, а мережа маршрутів сформувалась у містах історично і вже не відповідає вимогам сучасності. Головна мета – розробка алгоритму, що на основі матриці кореспонденцій і графа вулично-дорожньої мережі міг знайти оптимальний (або близький до оптимального) набір маршрутів громадського транспорту. Результат роботи - реалізація алгоритму пошуку оптимального набору маршрутів громадського транспорту методами колективного інтелекту мовою Python та порівняння роботи цього алгоритму з іншими алгоритмами на тестовому прикладі.The thesis concentrates on the problem of development of algorithm for solving the urban transit routing problem using collective intellig ence methods. Different existing optimization criteria and approaches to solving of the problem is considered. Public transport is one of the most important branches of city life support, from the operation of which considerably depend the quality of life , the efficiency of the industries of the city and the possibility of using its urban and socio - economic potential. But now in Ukraine public transport is insufficiently developed, the network of routes in cities formed mostly historically and no longer me ets today’s requirements. The main objective of the project is to develop an algorithm based on the correspondence matrix and graph the road network, that would be able to find an optimal (or close to optimal) set of public transport. The developed algor ithm for solving the urban transit routing problem is implemented with Python programming language and the results obtained by the algorithm are compared with results obtained by other algorithms on a test sample. Bachelor's thesis size 62 pages, 6 pictur es, 9 tables, 27 sources