This thesis develops a set of optimization-based approaches addressing wastewater system planning at regional level. Regional wastewater systems are required for the collection and the treatment of the wastewater that is generated in a region before being discharged into a water body. These systems are of crucial importance to guarantee the quality of the water bodies, which is vital for the promotion of a sustainable development. Because of this, and also because wastewater systems solutions are costly and very difficult to reverse, it is important that they are planned efficiently. When such planning is made at regional level, it is possible to obtain better solutions with regard to costs, taking advantage of scale economies, while achieving a better environmental performance.The proposed optimization models aim at finding the optimal layout for the sewer network, and for the location, type, and size of the pump stations and treatment plants to include in the system. The decisions on wastewater system planning involve two main issues: the setup and operation costs of infrastructure; and the water quality parameters to be met in the water body where the (treated) wastewater is discharged. The water quality varies along the river in accordance with the effluent discharges, and is assessed through environmental parameters such as dissolved oxygen, nitrogen, and phosphorus concentration.The basic optimization model applied consists in a deterministic formulation with a cost-minimization objective. The objective function is subjected to different constraints to ensure that the sewer network will be designed according to hydraulic laws and regulations. In the single-objective deterministic approach, the water quality goals are included through constraints to ensure that the effluent discharges from each treatment plant will not create environmental damage. To enhance the prospect of simultaneous accomplishment of both environmental and cost objectives, a multi-objective deterministic approach is also proposed, making possible to identify solutions that are a good compromise with regard to conflicting objectives. The multi-objective model is handled through the weighting method and consists of three objectives: minimization of capital costs; minimization of operating and maintenance costs; and maximization of dissolved oxygen.Wastewater systems are subjected to several sources of uncertainty. Various scenarios can occur in the future depending on the behavior of a variety of variables such as demographic or environmental. Different robust approaches are developed in this thesis, aimed at finding solutions that will perform well under any likely scenario. The source of uncertainties considered are the flow of the river that receives the wastewater generated in a given region and the amount of wastewater generated, that depends on the future population.This thesis is also concerned with model solving issues. The non-linear discrete optimization models are solved through an efficient simulated annealing algorithm enhanced with a local improvement procedure. The algorithm is termed efficient because its parameters were calibrated to ensure optimum or near-optimum solutions to the model within reasonable computing time. The calibration was performed using a particle swarm algorithm for a large set of test instances designed to replicate real-world problems.Finally, the thesis presents OptWastewater, an easy-to-use computer program designed to be a decision support tool incorporating the different optimization models. In addition to being used for all the calculations involved in this thesis, it aims at making this type of approaches more likely to be used in practice.
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