Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number ...
Proposed and developed is a service composition framework for decision-making under uncertainty, which is applicable to stochastic optimization of supply chains. Also developed is ...
This paper introduces disjunctive decomposition for two-stage mixed 0-1 stochastic integer programs (SIPs) with random recourse. Disjunctive decomposition allows for cutting plane...