One views demand response in industrial processes as the management of operating policies to accommodate variations in the availability and pricing of electricity from the grid. To find the optimal operating regimes and to facilitate the transitions in between such regimes in a costeffective manner, a mixed-integer nonlinear programming problem is often formulated. A full solution to this problem involves not only finding the optimal operating regimes but also determining the optimal control policies to ensure minimal transition costs; such solutions are often mathematically intractable. In this paper, a decomposition strategy is proposed to arrive at a feasible, albeit suboptimal, solution. The scheduling problem is first solved using a prefixed transition time to minimize the total operating cost; only the first scheduled transition of the obtained solution is implemented in the process, and optimization of controller parameters is then carried out to economically shape the transient profiles. When the first scheduled transition with the optimized controller parameters is completed, the scheduling and control problems are reformulated and resolved again in a receding-horizon optimization manner. A conceptual case study of a continuous stirred tank reactor demonstrates the key contributions and effectiveness of the strategy.