(1) Paper Title "Optimal Cost Design of Water Distribution Networks using Harmony Search" (2) Author Details Zong Woo Geem Environmental Planning and Management Program Johns Hopkins University 729 Fallsgrove Drive #6133 Rockville, MD 20850, USA Email: geem@jhu.edu Phone: +1-301-294-3893 (3) Corresponding Author Zong Woo Geem (4) Abstract This study presents a cost minimization model for the design of water distribution networks. The model uses a recently developed harmony search optimization algorithm while satisfying all the design constraints. The harmony search algorithm mimics a jazz improvisation process in order to find better design solutions, in this case pipe diameters in a water distribution network. The model also interfaces with a popular hydraulic simulator, EPANET, to check the hydraulic constraints. If the design solution vector violates the hydraulic constraints, the amount of violation is considered in the cost function as a penalty. The model was applied to five water distribution networks, and obtained designs that were either the same or cost 0.28 - 10.26% less than those of competitive meta-heuristic algorithms, such as the genetic algorithm, simulated annealing, and tabu search under the similar or less favorable conditions. The results show that the harmony search-based model is suitable for water network design. (5) Human Competitive Criteria A, B, F, G (6) Statement Today's highly capitalized societies require 'maximum benefit with minimum cost.' In order to achieve this goal, design engineers depend on cost optimization techniques. Design of water distribution networks is one of these efforts. Water network design involves determining the commercial diameter for each pipe in the network while satisfying the water demand and pressure at each node. The optimal cost design is the lowest cost design out of numerous possibilities. In order to find a low cost design in practice, experienced engineers have traditionally used trial-and-error (or rule of thumb) based on their intuitive 'engineering sense'. However, their approaches have not guaranteed 'optimal' or 'near-optimal' designs, which is why researchers have been interested in optimization methods. Alperovits and Shamir proposed a mathematical approach (a linear programming gradient method). This innovative approach was adopted and further developed by many researchers, such as Quindry et al., Goulter et al., Kessler and Shamir, and Fujiwara and Kang. Schaake and Lai used dynamic programming to search for a global optimum, while Su et al. and Lansey and Mays integrated gradient-based techniques with the hydraulic simulator KYPIPE, and Loganathan et al. and Sherali et al. introduced a lower bound. However, Cunha and Sousa indicated that the conversion of the values obtained by the aforementioned methods into commercial pipe diameters could worsen the quality of the solution and might not even guarantee a feasible solution. In order to overcome these drawbacks of mathematical methods, researchers such as Simpson et al., Cunha and Sousa, and Lippai et al. began to apply genetic or meta-heuristic algorithms, such as the genetic algorithm (GA), simulated annealing (SA), and tabu search (TS) to water network design. These algorithms evolved into more robust optimization models because they could obtain commercial diameters. Recently, Geem et al. developed a nature-inspired harmony search (HS) optimization algorithm that uses an analogy with the jazz improvisation process. The HS has been applied to various benchmarking and real-world optimization problems with success, including the traveling salesperson problem, six-hump camel back function, banana function, flood routing parameter calibration, truss structure design, and school bus routing. This research applied a HS algorithm to the optimal cost design of various real-world water distribution networks while considering the pressure and water demand constraints. (A) The result was patented as an invention in the past, is an improvement over a patented invention, or would qualify today as a patentable new invention. This Harmony Search-based model can be a patentable new invention which provides engineers with a cost optimization tool for the the water network design. (B) The result is equal to or better than a result that was accepted as a new scientific result at the time when it was published in a peer-reviewed scientific journal. One of referees who reviewed this paper mentioned, "The problem of water distribution networks cost minimization is very well known and the literature during these last twenty-five years has shown us many ways of tackling it. As a method for achieving global optimal solutions has not yet been found, it is important to try new methods. The approach used in this paper is a novel approach. The results provided are very promising." Harmony Search was successfully applied to the design of various water distribution networks, producing lower cost solutions than those of competing mathematical, evolutionary, or meta-heuristic algorithms as well as original trial-and-error method. The resulting costs obtained by the HS for the five water distribution were either the same or 0.28 - 10.26% less than those of competitive evolutionary and meta-heuristic algorithms, such as the GA, SA, and TS. The compared previous results were published in famous peer- reviewed scientific journals in water engineering field such as - Journal of Water Resources Planning and Management, ASCE - Journal of Environmental Engineering, ASCE - Journal of Hydraulic Engineering, ASCE - Journal of Infrastructure Systems, ASCE - Journal of Computing in Civil Engineering, ASCE - Water Resources Research (F) The result is equal to or better than a result that was considered an achievement in its field at the time it was first discovered. Since late 1960s, optimal water network design has been developed. But, still researchers try to find better and robust methodology. Harmony Search is one of latest one. (G) The result solves a problem of indisputable difficulty in its field. Even simple water network design such as design of two-loop network requires a complete enumeration of 14^8 = 1.48 x 10^9 different network designs, thus making this design difficult to solve. (7) Full Citation Author Name : Geem, Zong Woo Publication Date : In Press Name of Journal : Engineering Optimization Name of Editor : Prof. Andrew Templeman Publisher Name : Taylor & Francis Group