This works aims to demonstrate that hierarchical integration of planning and scheduling of industrial waste incineration improves the energy efficiency of the process, compared to available scheduling approaches. Through the integration with planning models, scheduling models can rely on more far-sighted information; therefore, energy deficits and excesses can be better compensated in the long run. Subsequently, the auxiliary fuel consumption of the incineration process can be further reduced, which leads to an overall increase of the energy efficiency. Planning and scheduling models are formulated as mixed-integer linear programming (MILP) problems with discrete time representation, based on single, uniform grids. The considered waste incineration system consists of storage tanks, a complex piping network, tank wagons for waste transport, unloading stations, and firing lances of incineration units. The conducted industrial case studies reveal substantial improvement potential of daily empirically based waste incineration routines and show that systematic integration of planning and scheduling outperforms consecutive stand-alone scheduling, of industrial waste incineration both economically and environmentally by reducing auxiliary fuel usage and CO2 emissions per ton of waste treated, by 16% and 1%, respectively.