scholarly journals A two-stage evolutionary optimization approach for an irrigation system design

2016 ◽  
Vol 19 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Milan Cisty ◽  
Zbynek Bajtek ◽  
Lubomir Celar
Keyword(s):  
Water Distribution ◽  
Irrigation System ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Search Space ◽  
Optimization Method ◽  
Global Optimum ◽  
Optimization Approach ◽  
Nsga Ii ◽  
Irrigation Network

In this work, an optimal design of a water distribution network is proposed for large irrigation networks. The proposed approach is built upon an existing optimization method (NSGA-II), but the authors are proposing its effective application in a new two-step optimization process. The aim of the paper is to demonstrate that not only is the choice of method important for obtaining good optimization results, but also how that method is applied. The proposed methodology utilizes as its most important feature the ensemble approach, in which more optimization runs cooperate and are used together. The authors assume that the main problem in finding the optimal solution for a water distribution optimization problem is the very large size of the search space in which the optimal solution should be found. In the proposed method, a reduction of the search space is suggested, so the final solution is thus easier to find and offers greater guarantees of accuracy (closeness to the global optimum). The method has been successfully tested on a large benchmark irrigation network.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

Design Optimization Method for MR-Brake Actuators

2011 ◽  
Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc
Keyword(s):  
Optimal Solution ◽  
Volume Ratio ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Friction Torque ◽  
Element Analysis ◽  
Taguchi Design Of Experiments ◽  
Variable Friction ◽  
Electronically Controllable

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.

scholarly journals An Inverse Transient-Based Optimization Approach to Fault Examination in Water Distribution Networks

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1154
Author(s):  
Chao-Chih Lin ◽  
Hund-Der Yeh
Keyword(s):  
Water Distribution ◽  
Large Scale ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Small Scale ◽  
Optimization Approach ◽  
Promising Technique ◽  
Preliminary Screening ◽  
Detection Approach ◽  
Symbiotic Organism Search

This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A modified steady hydraulic model considering the effects of pipe aging within a system is used to determine the steady nodal heads and piping flow rates. After applying a transient excitation, the transient behaviors in the system are analyzed using the method of characteristics (MOC). A preliminary screening mechanism is adopted to sift the initial organisms (solutions) to perform better to reduce most of the unnecessary calculations caused by incorrect solutions within the PEOS framework. Further, a symbiotic organism search (SOS) imitates symbiotic relationship strategies to move organisms toward the current optimal organism and eliminate the worst ones. Two experiments on leak and blockage detection in a single pipeline that have been presented in the literature were used to verify the applicability of the proposed approach. Two hypothetical WDNs, including a small-scale and large-scale system, were considered to validate the efficiency, accuracy, and robustness of the proposed approach. The simulation results indicated that the proposed approach obtained more reliable and efficient optimal results than other algorithms did. We believe the proposed fault detection approach is a promising technique in detecting faults in field applications.

scholarly journals Single-reservoir operating rules for a year using multiobjective genetic algorithm

2008 ◽  
Vol 10 (2) ◽  
pp. 163-179 ◽  
Author(s):  
Taesoon Kim ◽  
Jun-Haeng Heo ◽  
Deg-Hyo Bae ◽  
Jin-Hoon Kim
Keyword(s):  
Genetic Algorithm ◽  
Piecewise Linear ◽  
Search Space ◽  
Optimization Method ◽  
Optimal Number ◽  
Current Status ◽  
Nsga Ii ◽  
Multiobjective Genetic Algorithm ◽  
Operating Rules ◽  
Operating Rule

A monthly operating rule for single-reservoir operation is developed in this study. Synthetic inflow data over 100 years are generated by using a time series model, AR(1), and piecewise-linear operating rules consisting of 4 and 5 linear lines are found using the implicit stochastic optimization method. In order to consider multiobjective functions in reservoir system operation, a multiobjective genetic algorithm (NSGA-II) is adopted to obtain the optimization results. The search space of NSGA-II is carefully refined using frequency analysis of historical data, and the relationship between inflow and constraints is also investigated. It is determined that 4 and 5 segments are the optimal number of segments for the piecewise-linear operating rule, and the effect of random number seeding on NSGA-II is evaluated. Six years of historical inflow data are used for the simulation model and the results show that the developed operating rule would handle various inflow series. As a result, probabilistic reservoir storage forecasts can be provided to a system operator so as to enable the operator to evaluate the current status of a reservoir quantitatively.

Nesting Arbitrary Shapes Using Geometric Mating

2002 ◽  
Vol 2 (3) ◽  
pp. 171-178
Author(s):  
Chan Yu ◽  
Souran Manoochehri
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Computation Time ◽  
Search Space ◽  
Optimization Method ◽  
The Other ◽  
Reasonable Time ◽  
Common Features ◽  
Object Relative ◽  
Arbitrary Shapes

A genetic algorithm-based optimization method is proposed for solving the problem of nesting arbitrary shapes. Depending on the number of objects and the size of the search space, realizing an optimal solution within a reasonable time may not be possible. In this paper, a mating concept is introduced to reduce the solution time. Mating between two objects is defined as the positioning of one object relative to the other by merging common features that are assigned by the mating condition between them. A constrained move set is derived from a mating condition that allows the transformation of the object in each mating pair to be fully constrained with respect to the other. Properly mated objects can be placed together, thus reducing the overall computation time. Several examples are presented to demonstrate the efficiency of utilizing the mating concept to solve a nesting optimization problem.

scholarly journals Methodological Advances in the Design of Photovoltaic Irrigation

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2313
Author(s):  
Martín Calero-Lara ◽  
Rafael López-Luque ◽  
Francisco José Casares
Keyword(s):  
Rotational Speed ◽  
Hydraulic System ◽  
Water Distribution ◽  
Energy Requirement ◽  
Water Distribution Network ◽  
Irrigation Network ◽  
Daily Work ◽  
Photovoltaic Power ◽  
Irrigation Time ◽  
Energy Balances

In this study, an algorithm has been developed that manages photovoltaic solar energy in such a manner that all generated power is delivered to the system formed by a pump and irrigation network with compensated emitters. The algorithm is based on the daily work matrix that is updated daily by considering water and energy balances. The algorithm determines an irrigation priority for the sectors of irrigation of the farm based on programmed irrigation time and water deficits in the soil and synchronises the energy produced with the energy requirement of the hydraulic system according to the priority set for each day, obtaining the combinations of irrigation sectors appropriate to the photovoltaic power available. It takes into account the increment/decrease in the pressure of the water distribution network in response to increases/decreases in photovoltaic energy by increasing/decreasing the rotational speed of the pump, thus increasing/decreasing the power transferred to the system. The application to a real case of a 10-hectare farm divided into four sectors implies an efficient use of the energy of 26.15% per year and savings in CO2 emissions of 6.29 tonnes per year.

scholarly journals Fuzzy optimization based Water Distribution Network design using Self-Adaptive Cuckoo Search Algorithm

2021 ◽  
Author(s):  
A. Vasan ◽  
K. Srinivasa Raju ◽  
B. Sriman Pankaj
Keyword(s):  
Membership Function ◽  
Water Distribution ◽  
Search Algorithm ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions

Abstract Water Distribution Network(s) (WDN) design is gaining prominence in the urban planning context. Several factors that play a significant role in design are uncertainty in data, non-linear relation of head loss & discharge, combinatorial nature of the problem, and high computational requirements. In addition, many conflicting objectives are possible and required for effective WDN design, such as cost, resilience, and leakage. Most of the research work published has used multiobjective evolutionary optimization in solving such complex WDN. However, the challenge of such population based evolutionary approaches is that they provide multiple trade-off Pareto optimal solutions to the decision-maker who will have to choose another set of techniques to arrive at a single optimal solution. The present study employs a fuzzy optimization approach that would provide a single optimal WDN design for Hanoi and Pamapur, India. Maximization of network resilience (NR) and minimization of network cost (NC) are employed in a multiobjective context. Later, minimization of network leakages (NL) is also incorporated, leading to three objective problems. Hyperbolic Membership Function (HMF), Exponential Membership Function (EMF), and Non-linear Membership Function (NMF) are employed in Self-Adaptive Cuckoo Search Algorithm based fuzzy optimization. HMF is found suitable to determine the best possible WDN design for chosen case studies based on the highest degree of satisfaction. HIGHLIGHT Most of the research conducted till now have used evolutionary multiobjective optimization in solving WDNs. But, the challenge of such evolutionary approaches is that they provide multiple trade-off pareto optimal solutions to the decision maker who will have to further choose another methodology to converge to a single optimal solution. The proposed methodology would simplify the decision-making process for an engineer.

A New Global Optimization Method for Simultaneous Computation on Expensive Black-Box Functions

2003 ◽  
Author(s):  
Liqun Wang ◽  
Songqing Shan ◽  
G. Gary Wang
Keyword(s):  
Global Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Global Optimum ◽  
Black Box ◽  
Efficient Global Optimization ◽  
Global Optimization Method ◽  
Global Optimization Methods

The presence of black-box functions in engineering design, which are usually computation-intensive, demands efficient global optimization methods. This work proposes a new global optimization method for black-box functions. The global optimization method is based on a novel mode-pursuing sampling (MPS) method which systematically generates more sample points in the neighborhood of the function mode while statistically covers the entire search space. Quadratic regression is performed to detect the region containing the global optimum. The sampling and detection process iterates until the global optimum is obtained. Through intensive testing, this method is found to be effective, efficient, robust, and applicable to both continuous and discontinuous functions. It supports simultaneous computation and applies to both unconstrained and constrained optimization problems. Because it does not call any existing global optimization tool, it can be used as a standalone global optimization method for inexpensive problems as well. Limitation of the method is also identified and discussed.

scholarly journals An investigation of the possible scenarios for the optimal locating of quality sensors in the water distribution networks with uncertain contamination

2020 ◽  
Vol 18 (5) ◽  
pp. 704-721
Author(s):  
Hamideh Jafari ◽  
Taher Rajaee ◽  
Sara Nazif
Keyword(s):  
Water Consumption ◽  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Contaminated Water ◽  
Nsga Ii ◽  
Minimum Number ◽  
Contamination Event ◽  
Population Ratio

Abstract One of the ways to reduce the risk of contaminated water consumption is to optimally locate the quality sensors. These sensors warn users in the case of contamination detection. Analyzing the actual conditions of the contamination which enters the network is faced with many uncertainties. These uncertainties include the dose of contamination, time and location of its entry which have received less attention. Also, the uncertainty in the nodes' water demand causes changes in the distribution and contamination diffusion within the network. The main impetus of the present study is to determine the optimal quality sensor locations in the water distribution network in order to reduce the damage caused by contaminated water consumption prior to the contamination event detection. For this purpose, a parameter is defined as the maximum possible damage for calculating which the vulnerability and importance of the nodes have been considered in addition to the uncertainties in the location and time of the contamination entry. The importance of each node differs from that of other ones. Ranking the importance of the nodes is influenced by both land use and covered population ratio. In this study, six scenarios are defined for the contamination event in the water distribution network. These scenarios consider the effects of varying pollutant dose and the contamination input from nodes which are prone to its entry. Also, the NSGA-II has been utilized in order to minimize the damage with minimum number of sensors. The proposed model is evaluated on a real network in Iran. The results indicate that adding only one or two contamination warning sensors to the proposed locations can lead to the decreasing damage caused by the contaminated water consumption from 54 to 82%. According to the proposed method, the best answer for scenarios 1–6 was obtained for 7, 6, 6, 2, 2 and 2 sensors, respectively. The results showed that the slope of the pollution rate diagram does not change much from 6 sensors upwards in the first three scenarios, and from 4 sensors upwards in the second three scenarios. In scenarios 1–3, with 7, 6 and 6 sensors, respectively, in different nodes, the best placement is for 203–224 equivalent attack population, and in scenarios 4–6, with sensors in nodes 4 and 43, the best placement is for 225–279 equivalent attack population.

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