Temporal Decomposition Scheme for Nonlinear Multisite Production Planning and Distribution Models

Abstract

In this paper we propose a multiperiod nonlinear programming model for the production planning and product distribution of several continuous multiproduct plants that are located in different sites and supply different markets. The unique feature of the proposed model is that each plant is represented through nonlinear process models. To solve the resulting large-scale model, we present two solution techniques based on Lagrangean decomposition. Spatial decomposition is based on the idea of dualizing interconnection constraints between the plants and markets in order to be able to optimize each site and market individually. For the temporal decomposition, the interconnection constraints are defined between each time period through the inventory variables so that the entire production and distribution plan can be optimized independently in each time period. It is shown that the proposed decomposition methods yield significant computational savings, and temporal decomposition is shown to be the superior decomposition approach in terms of faster computational times and tighter bounds to the optimal solutions.

Process Supply Chains Management – Where are We? Where to Go Next?

“…From that time onward, several works on the process SCs addressed the presence of production and distribution for simultaneous activities. This is the case of the works presented by Kallrath (2002), Tsiakis and Papageorgiou (2008), Jackson and Grossmann (2003), Naraharisetti et al (2008), You and Grossmann (2008), Kallrath (2008), Lainez et al (2009), and Naraharisetti and Karimi (2010). Different issues have been addressed such as facility location and relocation, production and distribution design and planning, supply contracts, and capital generation as well as investment and disinvestment.…”

Advances in mathematical programming models for enterprise-wide optimization

“…The spatial integration of geographically distributed manufacturing and inventory facilities in supply chains leads to large-scale problems that often require the application of specialized decomposition techniques (e.g. Graves, 1982;Gupta and Maranas, 1999;Jackson and Grossmann, 2003;Neiro and Pinto, 2006;Li and Ierapetritou, 2010 …”

Optimal Design and Operational Planning of Responsive Process Supply Chains

“…Constraints (1) to (8) determine the network structure, constraints (9) to (14) refer to the operational planning constraints, constraints (15) to (30) …”