A Multi-Stage Stochastic Integer Programming Approach for Capacity Expansion under Uncertainty
Journal of Global Optimization
Mathematical Programming Models and Formulations for Deterministic Production Planning Problems
Computational Combinatorial Optimization, Optimal or Provably Near-Optimal Solutions [based on a Spring School]
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
A Lagrangian heuristic for satellite range scheduling with resource constraints
Computers and Operations Research
Relax-and-fix decomposition technique for solving large scale grid-based location problems
Computers and Industrial Engineering
Hi-index | 0.00 |
This paper addresses a particular stochastic lot-sizing and scheduling problem. The evolution of the uncertain parameters is modelled by means of a scenario tree and the resulting model is a multistage stochastic mixed-integer program. We develop a heuristic approach that exploits the specific structure of the problem. The computational experiments carried out on a large set of instances have shown that the approach provides good quality solutions in a reasonable amount of time.