In the present paper, a physics-inspired metaheuristic algorithm is presented to solve multi-objective optimization problems. The algorithm is developed based on the concept of Newtonian cooling law that recently has been employed by the Thermal Exchange Optimization (TEO) algorithm to efficiently solve single-objective optimization problems. The performance of the multi-objective version of TEO (MOTEO) is examined through bi- and tri-objective mathematical problems as well as bi-objective structural design examples. According to the comparisons between the MOTEO and several well-known algorithms, the proposed algorithm can provide quality Pareto fronts with appropriate accuracy, uniformity and coverage for multi-objective problems.