Due to global competition and dynamic market environment, a major challenge in enterprisewide optimization [1-3] has become to simultaneously optimize the production planning and inventory control decisions for chemical complexes under demand and supply uncertainty [4, 5]. Because chemical complexes are usually composed of many interconnected processes and various chemicals, it is an important ...

The bullwhip effect has been well known since many years and often takes place in supply chains. It is caused by wrong order policy in real systems. The bullwhip effect can be demonstrated easily through the beer game. It was developed by the MIT in the 60s. All stages of the supply chain operate independently. The only decisions that can be taken in the particular stages of this simulation gam...

Sample average approximation (SAA) is a widely popular approach to data-driven decisionmaking under uncertainty. Under mild assumptions, SAA is both tractable and enjoys strong asymptotic performance guarantees. Similar guarantees, however, do not typically hold in finite samples. In this paper, we propose a modification of SAA, which we term Robust SAA, which retains SAA’s tractability and asy...

Closed loop supply chain aims at integrating return products in the traditional supply chain processes. The return flows generate new uncertain elements (returns and leadtimes) and optimization of inventory control in this context is a complex issue. Inventory policies have to generate good performances (service level, cost) and be easy to implement in practice. A supply chain model based on si...

Production-inventory games were introduced in [Guardiola, L.A., Meca, A., Puerto, J. (2008). Production-Inventory games: A new class of totally balanced combinatorial optimization games. Games Econom. Behav. doi:10.1016/j.geb.2007.02.003] as a new class of totally balanced combinatorial optimization games. From among all core-allocations, the Owen point was proposed as a specifically appealing ...

Successful implementation of an inventory optimization solution requires significant effort and can pose certain risks to companies implementing such solutions. Depending on the complexity of the requirements, the solution may also involve a substantial IT investment. In this paper, we present a cost-effective solution for inventory optimization that can be useful for small and mediumsized busi...

We analyze a continuous review stochastic inventory model in which orders placed with a make-to-order manufacturer can be shipped via two alternative freight modes differing in lead-time and costs. The costs of placing an order and using each freight mode exhibit economies of scale. We derive an optimal policy for utilizing the two freight modes for shipping each order. This freight mode decisi...

Most of the research on aggregate production planning has been focused on discrete parts manufacturing models. In environments where intermediate inventory cannot be stored, and multiple products are produced simultaneously using complex con$gurations of production machines, these models may produce erroneous results. In this paper, we present a con$guration-based formulation for one such manuf...

Vendor managed inventory is a continuous replenishment program that is designed to provide major cost saving benefits for both vendors and retailers. Previous research on this area mainly included single objective optimization models where the objective is to minimize the total supply chain costs or to maximize the total supply chain benefits. This paper presents a bi-objective mathematical mod...

The newsvendor model is perhaps the most widely analyzed model in inventory management. In this singleperiod model, the only source of randomness is the demand during the period and one tries to determine the optimal order quantity in view of various cost factors. We consider an extention where supply is also random so that the quantity ordered is not necessarily received in full at the beginni...