Conjunctive water use management is crucial and inevitable in some regions due to its positive socio-economic impacts on removing water quality problems, well balanceing of the related costs and assuring to well supplying water demands. But, on the other hand, the management of conjunctive use is necessary to make water resources sustainable, especially in arid and semi-arid regions. In this dissertation, the conjuctive surface-ground water use optimization problem is formulated and solved in order to present optimal operation rules as well as designing an optimal multi-crop pattern plan. Minimizing groundwater level variations and maximizing agricultural net benefits are two main goals of the optimization model. A novel hybrid Multi-Objective Evolutionary Algorithm (MOEA) named fuzzy Multi-Objective Particle Swarm Optimization (f-MOPSO) is designed to solve the optimization problem. Furthermore, two other hybrid MOEAs named GAO-III and LAO are developed to evaluate performance of the f-MOPSO in global search as the main weakness any version of the PSO algorithm is engaged with. All these novel algorothms along with a robust multi-swarm multi-objective PSO algorithm named VEPSO are employed to solve the conjunctive use problem on the Najafabad study sub-area, located in central Iran, on a long-term 10-year simulation period beginning from 2003-2004, ending in 2012-2013 water years. On average, the results obtained indicated increase in irrigation efficiency by 7%, decrease in water consumption per unit cultivated area by 23% and increase in the water productivity by 23%, all compared to the similar criteria observed in the study sub-area in the actual operation. Moreover, considering the crop prices, crop water requirements and the yield response factors as the most effective factors to form the optimal multi-crop pattern plan, the rice and wheat were identified the dominant crops, on average, receiving 46.74% overally of the cultivated area, whereas the onion was identified as the least interesting crop, receiving only 7.35% of the total annual cultivated area, ranked as the last crop in the optimal multi-crop pattern plan presented by the models. Finally a multi-criteria analysis performed on the best solution of each model revealed the superiority of f-MOPSO in solving non-linear, non-convex, complex and large-scale optimization problems, as compared to other algorithms, demonstrating the capability of this algorithm to be applied in all engineering real-world problems, especially in the water resources management problems. Keywords: 1- Conjunctive water use 2- Hybrid MOEAs 3- MOPSO 4- Fuzzy logic