To incorporate uncertainties in empty container repositioning problem, we formulate a two-stage stochastic programming model with random demand, supply, ship weight capacity and ship space capacity. The Sample Average Approximation (SAA) method is applied to approximate the expected value function. Several non-independent and identically distributed sampling schemes are considered to enhance th...

I this paper, we consider a class of two-stage stochastic optimization problems arising in the protection of vital arcs in a critical path network. A project is completed after a series of dependent tasks are all finished. We analyze a problem in which task finishing times are uncertain but can be insured a priori to mitigate potential delays. A decision maker must trade off costs incurred in i...

The hub location–allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human’s unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of ...

In this thesis, a Benders decomposition algorithm is designed and implemented to solve both deterministic and stochastic pooling problems to global optimality. Convergence of the algorithm to a global optimum is proved and then it is implemented both in GAMS and C++ to get the best performance. A series of example problems are solved, both with the proposed Benders decomposition algorithm and c...

We develop a scalable parallel implementation of the classical Benders decomposition algorithm for two-stage stochastic linear programs. Using a primal-dual, path-following algorithm for solving the scenario subproblems we develop a parallel implementation that alleviates the diiculties of load balancing. Furthermore, the dual and primal step calculations can be implemented using a data-paralle...

We consider the problem of approximating the expected recourse function for two-stage stochastic programs. Our problem is motivated by applications which have special structure such as an underlying network which allows reasonable approximations to the expected recourse function to be developed. In this paper, we show how these approximations can be improved by combining them with sample gradie...

In cloud computing, providing an optimal resource to user becomes more and more important. Cloud computing users can access the pool of computing resources through internet. Cloud providers are charge for these computing resources based on cloud resource usage. The provided resource plans are reservation and on demand. The computing resources are provisioned by cloud resource provisioning model...