Ho Min Lee

Battle of the Water Networks II

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems

Optimal cost design of water distribution networks using a decomposition approach

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

Mine blast harmony search: A new hybrid optimization method for improving exploration and exploitation capabilities

Abstract This paper proposes a hybrid optimization method that combines the power of the harmony search (HS) with the mine blast algorithm (MBA). The resulting mine blast harmony search (MBHS) uses MBA for exploration and HS for exploitation. The HS is inspired by the improvisation process of musicians, while the MBA is derived based on explosion of landmines. The HS used in the hybrid algorithm is an improved version, introducing a new concept for the harmony memory size, while the MBA is modified in terms of its mathematical formulation. Several numerical problems and benchmarks with many design variables and constraints are used to validate MBHS, and the optimization results are compared with those from various algorithms in the literature. The numerical results show that the proposed hybrid method provides better exploitation ability (especially in the final iterations) and enjoys mature convergence to the optimum solution.

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

ABSTRACT In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Hydraulic Simulation Techniques for Water Distribution Networks to Treat Pressure Deficient Conditions

AbstractHydraulic analysis schemes for water distribution networks can be divided into demand-driven analysis (DDA) and pressure-driven analysis (PDA) according to the ways of calculating available outflow at nodes based on the assumption of nodal withdrawal estimation. Gradient algorithm-based numerical analysis schemes are generally used for these two types of hydraulic analysis. However, in abnormal conditions where hydraulic conditions rapidly change due to pipe damages or sudden increases in demands, the numerical solutions often derive unrealistic results that could lead to decision-making errors. In this study, the problems that may occur in hydraulic analysis of abnormal conditions were identified through sample cases using DDA and PDA models; then, the modification techniques resolving the simulation problems, the negative pressure in DDA and the total head reverse in PDA, were suggested. The proposed methods were verified by applying them to sample case study simulations. The application results...

Development and Application of Pressure Driven Analysis Model based on EPANET

Hydraulic analysis of water distribution systems (WDS) is divided into two types, one is Demand Driven Analysis (DDA) which applies to a steady state condition and other is Pressure Driven Analysis (PDA) which applies to an abnormal condition. In DDA, it is assumed that available discharge in demand nodes is always equal to the required discharge, and the assumption is suitable for a steady state condition. However, in abnormal conditions such as pipe failure or excess of demand, DDA model may produce unrealistic outputs such as negative pressure, so application of PDA model is required. The Gradient Algorithm used for DDA in EPANET was improved to develop a PDA model based on the Global Gradient Algorithm. Additionally, the developed model was applied to evaluate the emergency water supply plan of a large block system in Yeong Wol. The results showed to 66~100% of the total network demand was available in the emergency scenarios of failure in each reservoir. The developed PDA model is capable to solve negative pressure problem shown in existing DDA model and to analyse evaluation of emergency water supply plan with high reliability.

Optimal Leakage Detection Model of Water Distribution Systems Using Semi-Pressure Driven Analysis and Harmony Search

During maintenance and managing of water distribution systems, reducing water losses is a critical component. To achieve reduction of water losses, active leakage management is required. In this study, we propose optimal leakage detection model, which is the combination of simulation of hydraulic analysis and optimization technique. Through the use of hydraulic analysis method can able to achieve in creating a real-life based Semi-Pressure Driven Analysis (Semi-PDA) model without having to use the highly uncertain Head Outflow Relationship (HOR) is applied. EPANET2 created a model of emitter coefficient`s optimization, and it decides leakage location. For optimization technique, Harmony Search (HS) is applied that was developed in Korea and has been used in various cases recently. When we apply proposed method to sample network, it practically searches the leakage location. Especially, in optimization technique, we have a research of comparing the results of Harmony-Search (HS) and Genetic-Algorithm (GA); HS` result is more accurate. Also we verify that increasing of leakage location detection uncertainty by decreasing of number of observed data is less than GA. Therefore, suggested technique can be substituted to existing experiential leakage detection method. Therefore, this basic technology can be used as future proactive water resource management environment like Smart Water Grid.

Investigating the convergence characteristics of harmony search

Harmony Search optimization algorithm has become popular in many fields of engineering research and practice during the last decade. This paper introduces three major rules of the algorithm: harmony memory considering (HMC) rule, random selecting (RS) rule, and pitch adjusting (PA) rule, and shows the effect of each rule on the algorithm performance. Application of example benchmark function proves that each rule has its own role in the exploration and exploitation processes of the search. Good balance between the two processes is very important, and the PA rule can be a key factor for the balance if used intelligently.

KU Battle of Metaheuristic Optimization Algorithms 1: Development of Six New/Improved Algorithms

Each of six members of hydrosystem laboratory in Korea University (KU) invented either a new metaheuristic optimization algorithm or an improved version of some optimization methods as a class project for the fall semester 2014. The objective of the project was to help students understand the characteristics of metaheuristic optimization algorithms and invent an algorithm themselves focusing those regarding convergence, diversification, and intensification. Six newly developed/improved metaheuristic algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). This paper describes the details of the six developed/improved algorithms. In a follow-up companion paper, the six algorithms are demonstrated and compared through well-known benchmark functions and a real-life engineering problem.

Performance Comparison of Metaheuristic Optimization Algorithms Using Water Distribution System Design Benchmarks

Various metaheuristic optimization algorithms are being developed and applied to find optimal solutions of real-world problems. Engineering benchmark problems have been often used for the performance comparison among metaheuristic algorithms, and water distribution system (WDS) design problem is one of the widely used benchmarks. However, only few traditional WDS design problems have been considered in the research community. Thus, it is very challenging to identify an algorithm’s better performance over other algorithms with such limited set of traditional benchmark problems of unknown characteristics. This study proposes an approach to generate WDS design benchmarks by changing five problem characteristic factors which are used to compare the performance of metaheuristic algorithms. Obtained optimization results show that WDS design benchmark problems generated with specific characteristic under control help identify the strength and weakness of reported algorithms. Finally, guidelines on the selection of a proper algorithm for WDS design problems are derived.