scholarly journals Redesign of stormwater collection canal based on flood exceedance probability using the ant colony optimization: study area of eastern Tehran metropolis

Author(s):  
Sara Azargashb Lord ◽  
Mojtaba Hamze Ghasabsarai ◽  
Maryam Movahedinia ◽  
Seied Mehdy Hashemy Shahdany ◽  
Abbas Roozbahani

Abstract An increase in stormwater frequency following the rapid development of urbanization has drawn attention to the mitigating strategies in recent decades. For the first time, the present study aims to conduct a local rehabilitation in stormwater collecting systems by (i) detecting the critical nodes along with the canal network and (ii) redesigning the critical canal reaches using Ant Colony Optimization (ACO) to create maximum capacity for flood discharge with minimum reconstruction cost while considering the probability of exceedance of the flood as a constraint. Hence, using the SWMM model, the flow in the collection system was simulated, and the inundation points in the study area in the eastern Tehran metropolis were determined. After determining the critical points, the hydraulic stimulation model for the selected canal flows was developed using HEC-RAS software to accurately simulate each critical bridge's flow. Then, the optimal parameters for the canal bed width and canal depth were obtained using ACO and defining a probability objective function using the flood probability exceedance as the redesign constraint. The results from the optimizer were compared with those of the LINGO nonlinear model. Finally, the operational performance of the redesigned system was evaluated using the optimal selected parameters. The results showed that in redesigning the studied canals, the two widening and deepening options are needed to obtain a discharge with sufficient flow capacity in various return periods (RPs). The optimization results for the first to third critical sections for a design discharge with a 100-year RPs showed that the calculated cost was 19.765(*106), 13.327(*106), and 43.139(*106) IR Rials (1USD = 202000IRR), respectively. For the selected sections, the optimal bed width is 6.97, 8.97, and 10.93 meters, and the optimal depth is 3.68, 4.81, and 4.04 meters, respectively. The results indicate that the local modification in the eastern flood control canal adequately improved inundation problem reduction in various RPs – i.e., for a 10-year RP, the number of node flooding dropped from 4 to zero, the inundated area from 17 percent to zero, and the overflow volume from (10–45) to zero. It also reduced overflow volume from (30–65), (43–74), and (70–92) in the status quo to (4–12), (11–27), and (24–36) percent for precipitations with 25, 50 and 100-year RPs, respectively.

2021 ◽  
Vol 7 (5) ◽  
pp. 1978-1990
Author(s):  
Mingli Chi

Objectives: With the rapid development of computer technology and network technology, school teaching and management also need to keep pace with the development of the times, and information construction is needed in teaching and management. In the process of campus informationization construction, it is required that all links can be developed in a balanced way, and the school should be built into a scientific platform of information education and teaching from both hardware and software aspects. Methods: Sports achievement management system is based on reducing the workload of physical education teachers, improving teaching efficiency, optimizing the process of students’ class selection, enhancing the identification of students taking part in examinations, saving manpower, financial resources and time compared with the traditional registration model. Results: The ant colony optimization algorithm has achieved encouraging results in solving the combinatorial optimization problem that the traditional optimization method is difficult to work. Therefore, using this algorithm to optimize the simulation analysis of the physical education curriculum management system has better matching characteristics. Conclusion: The system has the characteristics of friendly man-machine interface, easy operation, strong compatibility, fast running speed, etc. It has rich reports and powerful query statistics.


2012 ◽  
Author(s):  
Earth B. Ugat ◽  
Jennifer Joyce M. Montemayor ◽  
Mark Anthony N. Manlimos ◽  
Dante D. Dinawanao

2012 ◽  
Vol 3 (3) ◽  
pp. 122-125
Author(s):  
THAHASSIN C THAHASSIN C ◽  
◽  
A. GEETHA A. GEETHA ◽  
RASEEK C RASEEK C

Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Agusma Wajiansyah ◽  
Supriadi Supriadi

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.


2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.


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