We propose a data structure called the “cooling box” which can be used to efficiently process the energetic reasoning [1], [4] for the parallel machine scheduling problem and the Cumulative Scheduling Problem (CuSP) [2]. In this context, each task to schedule can be represented by an object whose resource demands vary according to the time. To efficiently process some adjustments of the release dates of the tasks, it is useful to identify the highest-priority task, i.e. the one using the highest resource quantity at a given time. The aim of the proposed data structure is to obtain a time complexity of O(n 2 ln C) [3] for these adjustments instead of O(n 2 C) [1], where C is the capacity of the cumulative resource and n is the number of tasks. Référence: 1. Baptiste, C. Le Pape and W. Nuijten, "Constraint-based scheduling applying constraint programming to scheduling problems", volume 39 of International Series in Operations Research and Management Science, 2001. 2. J. Carlier, Problèmes d’Ordonnancement à Contraintes de Ressources: algorithmes et complexité. 3. J. Carlier, E. Pinson and A. Sahli, "An (On2) algorithm for time-bound adjustments for the cumulative scheduling problem", Technical report université de technologie de Compiègne, 2019. 4. J. Erschler and P. Lopez, "Energy-based approach for task scheduling under time and resources constraints", In Proceedings of the 2 nd international workshop on project management and scheduling , pp. 115-121, 1990.