in Wiley Online Library (wileyonlinelibrary.com).Existing methods for process scheduling can be broadly classified as network-based or sequential. The former are used to address problems where different batches of the same or different tasks are freely mixed or split, whereas the latter are used to address problems where batch mixing/splitting is not allowed. A framework is proposed that allows us to: (1) express scheduling problems in facilities that consist of network and sequential, as well as continuous subsystems, (2) formulate mixed-integer programming (MIP) scheduling models for such problems, and (3) solve the resulting MIP formulations effectively. The proposed framework bridges the gap between network and sequential approaches, thereby addressing the major formulation challenge in the area of process scheduling, namely, the development of a framework that can be used to address a wide spectrum of problems. Keywords: process scheduling, mixed-integer programming
IntroductionThe increasing product customization and diversification in the chemical industry have led to the installation (or retrofit) of facilities where multiple products compete for limited resources (equipment units and utilities) and which can be operated in multiple modes. The flexibility of these so called multiproduct facilities allows for higher resource utilization, lower inventory costs, and better responsiveness to demand fluctuations. Nevertheless, these advantages can only be materialized if the production is planned well, a task which is hard mainly due to the increased flexibility, and, thus, multiplicity of solutions.To address this challenge, researchers in the area of process systems engineering (PSE) have developed a number of systematic scheduling approaches, typically mixed-integer programming (MIP) formulations. These approaches can be generally classified as: (1) network-based, used to address problems where batch mixing (blending) and splitting are allowed; and (2) sequential, or ordered-based, used to address problems where batch splitting and mixing are forbidden. Hence, there is no single approach that can be used to represent and address all scheduling problems. Furthermore, there is no method for the solution of problems in processes with different restrictions on batch splitting/mixing. Consequently, one of the two major outstanding challenges in the area of scheduling is the development of a framework capable of addressing all process scheduling problems. The second major challenge is the reduction of the computational requirements of scheduling methods. In this article, we address the former by developing a general strategy for process scheduling, which is based on the representation of network-based and sequential subsystems using a common formalism, and the formulation of a computationally effective MIP model for the unified problem.The article is structured as follows. In the next section, we review scheduling problems and solution methods and present motivation for our work. In the following two sections, we...