The drive towards sustainability has compelled the batch process industries to implement the concept of environmentally friendly plants. However, the temporal nature of processing in these processes obviates the application of traditional waste minimization, material recycling, or energy integration schemes. Further, most of the existing methodologies for generating sustainable alternatives are restricted to specific problems, such as reaction byproduct, wastewater, or solvent minimization. In this paper, we propose an intelligent simulation–optimization framework for identifying comprehensive sustainable alternatives for batch processes. We differentiate between wastes generated by the reaction–separation process and cleaning wastes. A P-graph-based approach is used for identifying the root cause of process waste generation and generating broad design alternatives. Specific variable-level design solutions are then identified and evaluated using process simulation. The cleaning wastes resulting from the optimized process are also minimized using a source-sink allocation method that allows design of recycle network structure. A multi-objective stochastic optimization method is used to integrate the analysis so that the overall process economic and environmental footprint is optimized. We illustrate the proposed methodology using a well-known literature case study involving reaction, distillation and washing operation.