in this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. a two-stage stochastic linear programming approach is used to maximize the expected profit. decisions such as the production amount, the inventory level of finished and semi-finished product, t...

For decades, the Beer Game has taught complex principles of supply chain management in a finished good inventory supply chain. However, services typically cannot hold inventory and can only manage backlogs through capacity adjustments. We propose a simulation game designed to teach service-oriented supply chain management principles and to test whether managers use them effectively. For example...

Product recovery has become significant business strategies to increase a competitive edge in and also the society. Parts from discarded products due rapid advancement post-consumer before & after end-of-life (EOL) are recovered reduce landfill waste have part of circular economy. is made possible with help Closed-loop supply chain (CLSC). This paper concentrates on multi-period, multi-prod...

remanufacturing is an industrial process that makes used products reusable. remanufacturing is a way to establish a closed-loop supply chain. one of the important aspects in both reverse logistics and remanufacturing is pricing of returned and remanufactured products (called cores) that it has been noticed in this paper. in addition, in this paper the researchers have tried to present a mathema...

In this work we propose a stochastic model for the design and planning of closed-loop supply chains. Uncertainties in demand and return volumes are modelled together with uncertain transportation costs. A two-stage stochastic programming is developed and a sensitivity analysis to the worst-case probability is performed in order to test the solution robustness. Finally, in order to prove the goo...

We develop multi-dimensional balancing algorithms to compute provably near-optimal capacity-expansion policies. These are the first approximation algorithms for multi-machine, multi-product systems facing stochastic, non-stationary and correlated demands. Our approach is computationally efficient and guaranteed to produce a policy with total expected cost no more than twice that of an optimal p...

It is common that when a stock out occurs at a retailer the customer may go to another retailer. This phenomenon is often referred to as the customer market search. This paper analyzes the one manufacturer two retailer supply chain while considering the customer market search behavior. Game theoretic models are built to investigate the implications of this phenomenon in scenarios where wholesal...