Cost savings and enhanced reliability for main rehabilitation and replacement

Abstract

Water utilities across the United States anticipate a growing need to rehabilitate and replace aging water mains because of a convergence of pipe life spans. Shortfalls in funding for this activity will contribute to an estimated water infrastructure funding gap of $480 billion over the next 20 years. The city of San Diego (California) Water Department (SDW) undertook this pilot study to determine whether significant cost savings could be achieved in its rehabilitation and replacement (R&R;) program by using genetic algorithm (GA) optimization. Wilson and colleagues discuss how the use of GA optimization will save SDW millions of dollars compared with simulation trial and error. During this study, the GA evaluated millions of trial solutions to develop low-cost alternatives that met all of the design and emergency criteria specified by SDW. The GA identified a near-optimal mix of new pipe and R&R; choices that were not only low cost but also redundant and reliable in the event of a source outage or a main break. Includes 11 references, figures.