Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm

TLDR

Shuffled Frog Leaping Algorithm (SFLA) is a population‑based meta‑heuristic inspired by natural memetics, used for discrete optimization and featuring a local search similar to particle swarm optimization. The paper applies SFLA to determine optimal discrete pipe sizes for new and expanded water distribution networks and introduces SFLANET, a model linking SFLA with EPANET. SFLANET implements SFLA by infecting ideas among individuals during local search, shuffling information between local searches to approach a global optimum, and applying this framework to literature network design problems. Initial tests of SFLANET produced promising results, suggesting the approach is effective.

Abstract

Shuffled Frog Leaping Algorithm (SFLA) is a meta-heuristic for solving discrete optimization problems. Here it is applied to determine optimal discrete pipe sizes for new pipe networks and for network expansions. SFLA is a population based, cooperative search metaphor inspired by natural memetics. The algorithm uses memetic evolution in the form of infection of ideas from one individual to another in a local search. The local search is similar in concept to particle swarm optimization. A shuffling strategy allows for the exchange of information between local searches to move toward a global optimum. This paper summarizes the development of SFLANET, a computer model that links SFLA and the hydraulic simulation software EPANET and its library functions. Application of SFLANET to literature network design problems is then described. Although the algorithm is in its initial stages of development, promising results were obtained.