A novel synthesis framework is presented for evaluating different configurations and sequences of batch distillation processes and identifying the most appropriate flowsheet and cost-effective operating conditions simultaneously. A superstructure for batch distillation systems is constructed by employing a generic unit, which consists of segments of trays with top and bottom vessels attached to it, and accommodating three different types of integrated network design options for feed connections, sequencing connections, and configuration connections. This systematic formulation of batch distillation sequencing design problems allows not only the optimization of conventional flowsheets, but also the generation of novel configurations and sequences. The optimization framework is based on an mixed-integer nonlinear programming (MINLP) problem, which is effectively solved with a hybrid optimization method using simulated annealing and sequential quadratic programming (SA-SQP). Case studies are presented to demonstrate how the proposed approach can be applied in practice to improve cost-effectiveness of batch distillation systems.