This work addresses the indirect heat integration (i.e. resorting to intermediate heat storage) and the direct heat integration (i.e. heat exchanges between coexisting process streams) of batch processes. Tools and methods for the targeting of these two limiting cases of heat integration are proposed, and completed by the development and the application of an automatic design & optimization methodology using the Struggle genetic algorithm (GA). A brewery process is used to demonstrate the feasibility and the practical relevance of the proposed indirect heat integration models. The fluctuations of the process schedule and their effects on the optimal solutions are not modelled (the indirect heat integration is known to feature an inherently low sensitivity). The rescheduling opportunities are not searched for. For the indirect heat integration, fixed temperature/variable mass inventory heat storage units (HSUs) are applied. Two models of indirect heat recovery schemes (IHRSs) are proposed : one based on a closed heat storage system, another built around an open storage system suitable e.g. for food and beverages industries. The inequality constraints of the IHRS models are automatically met owing to an appropriate definition of the decision variables managed by the GA. A rough preadjustment of the mass balance equality constraints on HSUs is achieved by a preliminary stage of heat recovery (HR) maximization before actually minimizing the total batch costs (TBCs). Optimization runs and theoretical considerations on the generation & replacement strategy of Struggle demonstrate that the structural and the parametric variables cannot be efficiently optimized within a single level, resulting in a two-levels optimization scheme. The automatically designed closed storage IHRS solutions for the brewing process are as good as the solutions obtained by another author using a combinatorial method followed by a post-optimization stage. The open storage IHRS is 13 % cheaper while the HR increases by 12 %. Optimizing the IHRS on a one-week period (including the non-periodic start-up & shut-down phases) results in an even more realistic solution, featuring a significantly different trade-off between energy, HSU capacities and HEX areas. A GA based, two-levels optimization scheme is proposed for the design of direct batch heat exchanger networks (HENs). The HEN structures, managed by the upper-level GA, do not include stream splitting. The re-use of HEX units across time slices is a key issue and a methodology to specify the actually possible structural changes by repipe or resequence is proposed, accounting for the thermo-physical compatibility, chemical compatibility, and process schedule constraints. The optimum operation of an existing HEN during each time slice has been analysed and a sound solution procedure is proposed.