Rebirthing genetic algorithm for storm sewer network design

Application of standard binary coded genetic algorithms for the solution of problems with continuous design variables requires discretization of the continuous decision variables. Coarse discretization of the design variables could adversely affect the final solution, while finer discretization would increasingly enlarge the scale of the problem, leading to higher computation cost. A rebirthing procedure is used in this paper as a remedy for the problem just outlined. The method is based on the idea of limiting the originally wide search space to a smaller one once a locally converged solution is obtained. The smaller search space is designed to contain the locally optimum solution at its center. The resulting search space is refined and a completely new search is conducted to find a better solution. The procedure is continued until no refinement is necessary or no improvement could be made by further refinement. The method is applied to a benchmark problem of a storm water network design, and the results are compared with those of the existing method. The method is shown to be very effective, efficient and insensitive to the population size of the genetic search and the search space size of the optimization problem