Cette étude concerne l’optimisation multiobjectif de réseaux d’eau industriels via des techniques de programmation mathématique. Dans ce travail, un large éventail de cas est traité afin de proposer des solutions aux problèmes de réseaux les plus variés. Ainsi, les réseaux d’eau monopolluants sont abordés grâce à une programmation mathématique linéaire (MILP). Cette méthode est ensuite utilisée dans le cadre d’une prise en compte simultanée des réseaux d’eau et de chaleur. Lorsque le réseau fait intervenir plusieurs polluants, le problème doit être programmé de façon non linéaire (MINLP). L’optimisation multicritère de chaque réseau est basée sur la stratégie epsilon-contrainte développée à partir d’une méthode lexicographique. L’optimisation multiobjectif suivie d’une réflexion d’aide à la décision a permis d’améliorer les résultats antérieurs proposés dans la littérature de 2 à 10% en termes de consommation de coût et de 7 à 15% en ce qui concerne la dépense énergétique. Cette méthodologie est étendue à l’optimisation de parcs éco-industriels et permet ainsi d’opter pour une solution écologique et économique parmi un ensemble de configurations proposées. / This study presents a multiobjective optimization of industrial water networks through mathematical programming procedures. A large range of various examples are processed to propose several feasible solutions. An industrial network is composed of fixed numbers of process units and regenerations and contaminants. These units are characterized by a priori defined values: maximal inlet and outlet contaminant concentrations. The aim is both to determine which water flows circulate between units and to allocate them while several objectives are optimized. Fresh water flow-rate (F1), regenerated water flow-rate (F2),interconnexions number (F3), energy consumption (F4) and the number of heat exchangers (F5) are all minimized. This multiobjective optimization is based upon the epsilon-constraint strategy, which is developed from a lexicographic method that leads to Pareto fronts. Monocontaminant networks are addressed with a mixed linear mathematical programming (Mixed Integer Linear Programming, MILP) model, using an original formulation based on partial water flow-rates. The obtained results we obtained are in good agreement with the literature data and lead to the validation of the method. The set of potential network solutions is provided in the form of a Pareto front. An innovative strategy based on the GEC (global equivalent cost) leads to the choice of one network among these solutions and turns out to be more efficient for choosing a good network according to a practical point of view. If the industrial network deals with several contaminants, the formulation changes from MILP into MINLP (Mixed Integer Non Linear Programming). Thanks to the same strategy used for the monocontaminant problem, the networks obtained are topologically simpler than literature data and have the advantage of not involving very low flow-rates. A MILP model is performed in order to optimize heat and water networks. Among several examples, a real case of a paper mill plant is studied. This work leads to a significant improvement of previous solutions between 2 to 10% and 7 to 15% for cost and energy consumptions respectively. The methodology is then extended to the optimization of eco-industrial parks. Several configurations are studied regarding the place of regeneration units in the symbiosis. The best network is obtained when the regeneration is owned by each industry of the park and allows again of about 13% for each company. Finally, when heat is combined to water in the network of the ecopark, a gain of 11% is obtained compared to the case where the companies are considered individually.