(614d) Integrated Planning and Scheduling of Multisite Production and Distribution Facilities

Modern process industries operate as a large integrated complex that involve multiproduct, multipurpose, and multisite production facilities serving a global market. The process industries supply chain can be defined to be composed of production facilities and distribution centers, where final products produced at production facilities are transported to distribution center to satisfy the customers demand. The multisite plants produce a number of products driven by market demand under operating conditions such as sequence dependent switchovers and resource constraints. Each plant within the enterprise may have different production capacity and costs, different product recipes, and different transportation costs to the markets according to the location of the plants. To maintain economic competitiveness in a global market, interdependences between the different plants, including intermediate products and shared resources need to be taken into consideration when making planning decisions. Furthermore, the planning model should consider not only individual production facilities constraints but also transportation constraints because in addition to minimizing the production cost, it’s important to minimize the costs of products transportation from production facilities to the distribution centers.

Thus, simultaneous planning of all activities from production to distribution stage is important in a multisite process industry supply chain [1]. To achieve enterprise wide optimization (EWO) in spatially distributed production facilities and distribution centers, interactions between different complexes should be taken into consideration and their optimization should be tackled simultaneously. In the recent years, multisite production and distribution planning problem has received lot of attention in the literature [2-4].

The planning problem covers a time horizon of few months to a year and is concerned with decisions such as production, inventory, and distribution whereas the scheduling problem 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. Since there is a significant overlap between different decisions levels, it is necessary to integrate planning and scheduling problems to achieve global optimal solutions for the entire supply chain [5]. For multisite facilities, the size and level of interdependences between these sites present unique challenges to the integrated tactical production planning and day-to-day scheduling problem and these challenges are highlighted by Kallrath, 2002  [6].

In this work, we focus on the integration of planning (medium-term) and scheduling (short-term) problems for the multiproduct plants that are located in different sites and supply different markets. In the recent years, the area of integrated planning and scheduling for single site has received much attention [7-9]. Even though most companies operate in a multi-site production manner, very limited attention has been paid on integrating planning and scheduling decisions for multi-site facilities.

In this work, we first propose an integrated planning and scheduling model for multisite production and distribution facilities that takes into consideration shared resources and intermediates between production facilities, transportation time between production facilities, between production site and distribution center, and in some rare case, between distribution centers. To account for the situations when due to production capacity limitations or raw material availability limitations, industry cannot satisfy the demand; we consider the option of hiring external contractors. The full-scale integrated planning and scheduling optimization model spans the entire planning horizon of interest and includes decisions regarding all the production sites, distribution centers, and transportation between them. Since the production planning and scheduling levels deal with different time scales, the major challenge for the integration using mathematical programming methods lies in addressing large scale optimization models. When typical planning horizon is considered, the integrated problem becomes intractable and a mathematical decomposition solution approaches are necessary. To effectively deal with complexity issues of the integrated problem, the block angular structure of the constraints matrix is exploited by relaxing the inventory constraints between adjoining time periods using the augmented lagrangian decomposition method. To resolve the issues of non-separable cross-product terms in the augmented lagrangian function, we apply diagonal approximation method. This decomposition then results in separable planning and scheduling problems for each planning period and for each production site. To illustrate the effectiveness of the proposed model and decomposition approach, we apply them to different sizes case studies.

 

References:

(1)        Shah, N., Single and multisite planning and scheduling: current status and future challenges. AIChE Symposium Series, 1998. 94(320): p. 75.

(2)        Verderame, P.M. and C.A. Floudas, Operational planning framework for multisite production and distribution networks. Computers & Chemical Engineering, 2009. 33(5): p. 1036-1050.

(3)        Jackson, J.R. and I.E. Grossmann, Temporal Decomposition Scheme for Nonlinear Multisite Production Planning and Distribution Models. Industrial & Engineering Chemistry Research, 2003. 42(13): p. 3045-3055.

(4)        Timpe, C.H. and J. Kallrath, Optimal planning in large multi-site production networks. European Journal of Operational Research, 2000. 126(2): p. 422-435.

(5)        Maravelias, C.T. and C. Sung, Integration of production planning and scheduling: Overview, challenges and opportunities. Computers & Chemical Engineering, 2009. 33(12): p. 1919-1930.

(6)        Kallrath, J., Planning and scheduling in the process industry. OR Spectrum, 2002. 24(3): p. 219-250.

(7)        Li, Z. and M.G. Ierapetritou, Rolling horizon based planning and scheduling integration with production capacity consideration. Chemical Engineering Science, 2010. 65(22): p. 5887-5900.

(8)        Li, Z. and M.G. Ierapetritou, Production planning and scheduling integration through augmented Lagrangian optimization. Computers & Chemical Engineering, 2010. 34(6): p. 996-1006.

(9)        Verderame, P.M. and C.A. Floudas, Integrated Operational Planning and Medium-Term Scheduling for Large-Scale Industrial Batch Plants. Industrial & Engineering Chemistry Research, 2008. 47(14): p. 4845-4860.