Optimum design of sewer networks with pump station using Genetic Algorithms

Abstract

The main aim of the current study is to develop a new model for the minimum cost of optimum design for a sewer network with pumping stations. The difficulty and relatively large number of nonlinear and discrete constraints in a sewer network with pump station design problems make their handling of extreme importance. For this purpose, an adaptive genetic algorithm (GA) model is proposed for the effective and efficient optimal design with a fixed layout so that each chromosome, consists of diameters, slopes of the pipes and pump indicators. In the present model, the pump locations are decided preliminary, then for each GA chromosome, the network characteristics including the diameters of pipes and slope for those pipes are determined. MATLAB code was used to perform the optimization model. Then a sewer network from previous literature was used to be designed as a benchmark example for the proposed method. It’s concluded that the proposed model has reached the optimal solution at the lowest cost and the fewest number of generations compared with previous methods in the literature.

Optimal design of sewage networks for Al-Jaffryah Quarter and Al-Kut Trade Center using genetic algorithms and spectral analysis of the river to know the effect of network waste.

“…The code for improvement was made based on a recent study that was carried out in Karbala Governorate. The local prices of the Wasit Sewers Directorate were relied upon, as well as the depths of special drilling when implementing the network (Atiyah et al 2021). The results of the Roulette wheel selection (RWS), and the One-Point Crossover (OPC) were used as the best of many methods in the relationship among the optimal design of the diameters of sewer pipes.…”

“…With dependence on the prices for the city of Kut, which were obtained as mentioned previously. [17] ∑ ( ) ∑ ∑…”

“…where, represents the overall cost of the sewer system (units), represents number of network pipes, indicates the number of network nodes, represents the length of 𝑡 pipes, is the diameter of 𝑡 pipes, is the downstream and upstream excavation depth of 𝑡 pipe, is the unit cost of construction related to every pipe, it is a function of its diameter ( ), represents the manhole's depth, indicates the unit construction cost of 𝑡 manhole, represents the discharge, and represents the coefficient of cost for the pump installing at the 𝑡 node. Table (3) It shows the special equations for calculating the cost for each pipe and manhole according to the conditions [17].…”

Hydraulic-based optimization algorithm for the design of stormwater drainage networks

“…Then, Sotoodeh used Fletcher-Reeves method and achieved the lowest overall cost for this portion of Iran's sewage system (Sotoodeh 2004). Other optimization techniques are used for the optimization of sewer networks, such as genetic algorithm (GA), hybrid techniques based on cellular automata, tabu search (TS) and simulated annealing (SA), ant colony optimization algorithm (ACOA) and tree-growing algorithm (TGA), spanning tree and modified particle swam optimization (PSO), mixed-integer linear programming (MILP) and others Bakhshipour 2012, 2015;Afshar and Rohani 2012;Afshar et al 2016;Yeh et al 2013;Emmerich et al 2013;Duque et al 2016;Navin and Mathur 2016;Safavi and Geranmehr 2017;Moeini 2017;Moeini andAfshar 2017, 2018;Hassan et al 2020;Saldarriaga et al 2021;Atiyah and Hassan 2021). When comparing the outcomes achieved through the utilization of genetic algorithm (GA) and TS to those obtained through alternative methods, it becomes evident that GA and TS yield optimal results with minimal network cost.…”