| Summary: | 碩士 === 立德管理學院 === 資源環境研究所 === 94 === The optimization method has been developed from traditional linear and non-linear programming to evolutionary algorithms in recent years, for example genetic algorithms (GAs), simulated annealing (SA), tabu search (TS) and the newest developed ant colony optimization (ACO). ACO has impressive achievements in making the application of combinatorial optimization problems. However, it hasn’t been applied to optimization of sewer network system so far. This research uses ACO to optimize the sewer network system. The excellent behavior of searching solved problems could let us have more chances to find optimal solution and test the important control parameters in order to provide a sound basis for parameter settings.
The simulation result shows that the optimal design basis on the best parameters, under design criteria and assumed conditions, the saving by using small-scale sewer network system is not apparent. However, the cost of using medium-scale sewer network system saves 5.6% under minimum cost and original design plan. It is helpful to design sewer network system and economize on budgets. As a result, the outstanding achievements of ACO applies to optimize sewer network system has been proved.
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