Parabolic trough collectors (PTCs) are highly efficient technologies for harnessing solar energy, used in applications such as power generation, water desalination, and residential cooling or heating. In desalination, PTC systems convert seawater into freshwater by reducing salinity. These systems have advanced into sophisticated Concentrated Solar Power (CSP) systems, with modeling and simulation providing insights for performance enhancement. Literature suggests various design improvements, focusing on optical and thermal properties, which can yield significant returns, especially in large-scale plants. This work proposes using the Grey Wolf Optimizer (GWO) algorithm for PTC design optimization. GWO, inspired by the hunting behavior of grey wolves, is adaptable, requires minimal initialization parameters, and effectively avoids local optima. The optimization targets thermal and exergetic efficiencies, with design variables including the inlet temperature and the diameters of the PTC receiver tube, while maintaining constant material volume to avoid additional costs. A multi-objective optimization approach was formulated and implemented in MATLAB, demonstrating efficiency in maximizing thermal and exergetic efficiencies. To validate the results reported using the proposed approach, the augmented ε-constraint method (AUGMENCON) is introduced, for the design and performance enhancement of PTCs. The proposed approach is beneficial for researchers aiming to analyze and enhance PTC performance, allowing them to select preferred optimal points from existing Pareto fronts for PTC design.