This paper explores the capabilities of Multi-objective Particle Swarm Optimization algorithm in a simulation-optimization model for solving waste load allocation problems. The main goals are total treatment costs, violation of the water quality standards and equity. In this research, the water quality simulation model is coupled with a multi-objective optimization model, MOPSO. In order to derive non-dominated solutions, two different optimization models are used. The first is referred to as the cost versus quality model and the second one also consider minimizing cost and inequity. For the each case, the trade-off curve (Pareto front) is derived and the best non-dominated solution on the trade-off could be selected by stakeholders and decision makers. The proposed model has been developed for Haraz River in the northern part of Iran which represented scenarios considering different interests and answered questions to modify scenarios according to the decision makers' ideas. Solutions were compared with NSGA-II, and the results demonstrate a suitable convergence and diversity of proposed algorithm.