Mid-term supply chain planning under demand uncertainty: customer demand satisfaction and inventory management

Abstract

This paper utilizes the framework of midterm, multisite supply chain planning under demand uncertainty (Gupta and Maranas, 2000) to safeguard against inventory depletion at the production sites and excessive shortage at the customer. A chance constraint programming approach in conjunction with a two-stage stochastic programming methodology is utilized for capturing the trade-off between customer demand satisfaction (CDS) and production costs. In the proposed model, the production decisions are made before demand realization while the supply chain decisions are delayed. The challenge associated with obtaining the second stage recourse function is resolved by first obtaining a closed-form solution of the inner optimization problem using linear programming duality followed by expectation evaluation by analytical integration. In addition, analytical expressions for the mean and standard deviation of the inventory are derived and used for setting the appropriate CDS level in the supply chain. A three-site example supply chain is studied within the proposed framework for providing quantitative guidelines for setting customer satisfaction levels and uncovering effective inventory management options. Results indicate that significant improvement in guaranteed service levels can be obtained for a small increase in the total cost.3

The Effects of Demand Pull Strategies on Sustainable Development in Manufacturing Industries

“…This investigation may guide a service company's interest in suitable quality activities. Gupta et al (2000) suggested a model for settlement amongst customer demand satisfaction and manufacturing costs. In the recommended model, the production choices are made before demand acknowledgment and on the other side, the inventory network choices are postponed.…”

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

“…In 2000, Gupta et al (2000) considered a mid-term, multi-site SC planning under demand uncertainty to safeguard against inventory depletion at the production sites and excessive shortage at the customer demand. In 2003, Gupta and Maranas (2003) developed a bilevel decision-making framework where production decisions are made "here-and-now" prior to the resolution of uncertainty, while the SC decisions are postponed in a "wait-and-see" mode.…”

A study on closed-loop supply chain model for parts reuse with economic efficiency

“…The profit maximization problem was modeled as a dynamic program. Gupta et al (2000) utilized a framework of mid-term, multisite supply chain planning under demand uncertainty to safeguard against inventory depletion at the production sites and excessive shortage at the customer. Banerjee et al (2001) examined the effects of two controlled partial shipment approaches within a single supplier, multiple customers supply chain network through a series of simulation experiments under different operating conditions, based on the number of customers and the variability of their order sizes.…”