Optimal Design of Sewer Network by Tabu Search and Simulated Annealing

Optimal sewer network designs are NP-hard and highly complicated nonlinear problems. Conventional optimization techniques often easily get bogged down in local optima and cannot successfully address such problems. In the past decades, heuristic algorithms with robust and efficient global-search capabilities have helped to solve continuous and discrete optimization problems and have demonstrated considerable promise. This study applied tabu search (TS) and simulated annealing (SA) to the optimization of sewer-network designs. As a case study, it applied to solve a benchmark sewer network optimization problem reported in the literature. The optimal configuration of TS and SA parameters were determined by systematically evaluating the relative computational performance of TS and SA. Characteristic analysis was undertaken and solution qualities from different algorithms were also compared. The results show that SA is able to obtain optimal sewer network designs better than those methods previously reported in the literature.