We consider the capacity planning of telecommunication networks with linear investment costs and uncertain future tra c demands. Transmission capacities must be large enough to meet, with a high quality of service, the range of possible demands, after adequate routings of messages on the created network. We use the robust optimization methodology to balance the need for a given quality of servi...

In this article, we elaborate on a budget constrained extension of the r -interdiction median problem with fortification (RIMF). The objective in the RIMF is to find the optimal allocation of protection resources to a given service system consisting of p facilities so that the disruptive effects of r possible attacks to the system are minimized. The defender of the system needs to fortify q fac...

Uncertain demand combined with a positive lead time for adding capacity creates the risk of capacity shortage during the lead time. Accurate shortage estimation is very important to determine a capacity expansion policy. In this paper, we investigate four kinds of option pricing methods to estimate the shortage during a fixed lead time under the assumption of an exponential trend for demand gro...

Railways around the world are facing capacity constraints. In North America, railway freight traffic has increased nearly 30% over the past 10 years, and this demand is projected to increase 88% by 2035. It is clear that network capacity has to be increased by a combination of several engineering options, but the question is how railroads can allocate investment in infrastructure in the best po...

We consider a supply chain in which one manufacturer sells a seasonal product to the end market through a retailer. Faced with uncertain market demand and limited capacity, the manufacturer can maximize its profits by adopting one of two strategies, namely, wholesale price rebate or capacity expansion. In the former, the manufacturer provides the retailer with a discount for accepting early del...

In this study, a dynamic inexact waste management (DIWM) model is developed for identifying optimal waste-flow-allocation and facility-capacity-expansion strategies under uncertainty and is based on an inexact scenario-based probabilistic programming (ISPP) approach. The DIWM model can handle uncertainties presented as interval values and probability distributions, and it can support assessing ...

Investment in capacity expansion remains one of the most critical decisions for a manufacturing organisation with global production facilities. Multiple factors need to be considered making the decision process very complicated. The purpose of this paper is to establish the state-of-the-art in multi-factor models for capacity expansion in manufacturing plants and networks. A three phase researc...

As the market expands, regulation to foster orderly growth of the industry begins to become fetters for further growth. In the 1980’s, mission was initiated in Japan to deregulate economic regulations of the domestic aviation market. In line with deregulation policy, airport capacity expansion was accelerated to facilitated growth of the market. In this paper, social welfare of deregulation and...

In this paper, the dynamic and complex nature of capacity expansion race is depicted by a non-linear dynamic system that parsimoniously captures the market moves of firms and their collective impacts on each firm and the industry as a whole. Three types of capacity expansion strategy (market preemption, pacing, and phase-out) are investigated using a non-linear dynamic simulation model. We argu...

In this paper, we develop a multi-objective stochastic programming approach for supply chain design under uncertainty. Demands, supplies, processing, transportation, shortage and capacity expansion costs are all considered as the uncertain parameters. To develop a robust model, two additional objective functions are added into the traditional comprehensive supply chain design problem. So, our m...