Rebirthing genetic algorithm for storm sewer network design

Application of standard binary coded genetic algorithms for the solution of problemswith continuous design variables requires discretization of the continuous decision variables. coarsediscretization of the design variables could adversely affect the final solution, while finer discretizationwould increasingly enlarge the scale of the problem, leading to higher computation cost. a rebirthingprocedure is used in this paper as a remedy for the problem just outlined. the method is based on the ideaof 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 resultingsearch space is refined and a completely new search is conducted to find a better solution. the procedure iscontinued until no refinement is necessary or no improvement could be made by further refinement. themethod is applied to a benchmark problem of a storm water network design, and the results are comparedwith those of the existing method. the method is shown to be very effective, efficient and insensitive tothe population size of the genetic search and the search space size of the optimization problem.