(496e) Integrated Production Planning and Scheduling of Multi-Site Batch Plants
The supply chain of a typical chemical company consists of a network of integrated production facilities and inventory centers supplying several distribution markets. To maintain economic competitiveness in today's global market, simultaneous planning of all activities from production to distribution is of great importance. The resulting planning decisions can be divided into three levels: strategic (long-term), tactical (medium-term), and operational (short-term). The long-term planning determines the infrastructure of the supply chain (e.g. facility location, transportation network) which involves decisions for the entire lifelong of the plant. The medium-term planning covers a time horizon of few months to a year and is concerned with decisions such as production, inventory, and distribution. Finally, short-term planning decision deals with issues such as assignment of tasks to units and sequencing of tasks in each unit which covers time horizon of few days to few weeks. However, there is a significant overlap between different decisions levels and thus it is necessary to integrate planning problems to achieve global optimal solutions for supply chain .
In this work, we focus on the integration of planning (medium-term) and scheduling (short-term) problems for the multi-product plants that are located in different sites and supply different markets. Plants at different locations produce a number of products driven by market demand. The optimal decisions at the production level and the interdependences between the different plants, including intermediate products and shared resources should be taken into account in an integrated manner. Similar problems have been addressed in the literature [2-4].
We present a full-space integrated planning and scheduling model for multi-site production plants. The resulting full-space model is large-scale involving integer and continuous variables and thus it is computationally very complex. To deal with the model complexity, we decompose the model into planning and scheduling level using Lagrangian decomposition technique. The resulting scheduling level problem can be further decomposed into site level problem via spatial decomposition. The spatial decomposition of production sites is based on the idea of dualizing interconnection constraints between sites in order to be able to optimize each production site individually. Results are presented for different case studies to illustrate the proposed scheme.
 Maravelias CT, Sung C. Integration of production planning and scheduling: Overview, challenges and opportunities. Computers & Chemical Engineering. 2009; 33: 1919-1930.  Wilkinson SJ, Cortier A, Shah N, Pantelides CC. Integrated production and distribution scheduling on a Europe-wide basis. Computers & Chemical Engineering. 1996; 20: S1275-S1280.  Sukoyo, Matsuoka S, Muraki M. Production Planning for Multi-site Batch Plants with the MILP Method. Journal of the Japan Petroleum Institute. 2004; 47: 318-325.  Jackson JR, Grossmann IE. Temporal Decomposition Scheme for Nonlinear Multisite Production Planning and Distribution Models. Industrial & Engineering Chemistry Research. 2003; 42: 3045-3055.