<p><?tk 2?>Recently, several industrial engineering practitioners have focused on sustainable manufacturing environments that arise in various real-world scenarios. Sustainability constraints are usually related to the consumption of non-renewable resources, energy tariffs, or carbon emissions. In this paper, we present an extensive computational evaluation of identical parallel machine scheduling problems with controllable processing times and limited resource constraints. We assess two objective functions: minimizing makespan and total tardiness. Given the NP-hardness of the variants under study, we develop two mixed-integer linear programming (MILP) models and three constraint programming (CP) models. Two statistics are used as performance indicators: the Average Relative Percentage Deviation and the Success Rate. Based on the computational evaluation of 2250 randomly generated test instances, the third CP model presented the best results for the makespan objective, and the second CP model returned the best solution for the total tardiness objective. Usually, the CP models outperformed the MILP models for most of the test instances under evaluation.</p> Graphical abstract