This paper presents a graph-theoretic approach for the scheduling of multipurpose batch plants with the objective to maximize economic performance indexes, such as throughput, revenue, and profit over a predefined time horizon. The approach is based on the S-graph framework, which has been previously applied in the scheduling of multipurpose batch plants for the optimization of time-based performance indexes, e. g., minimization of makespan. In contrast to most techniques published in the literature, the approach proposed in this paper does not require any presupposition of the number of time points or manipulation of the time horizon of interest, which renders it continuous in time. The optimization procedure is based on a guided search algorithm that is guaranteed to terminate at a global optimum. Furthermore, the proposed approach exploits structural uniqueness of the problem to improve computational efficiency, which is necessary for industrial-scale problems. Nonintermediate storage (NIS) operational policy is addressed in this paper.