Workforce planning in a lotsizing mail processing problem
Computers and Operations Research
Computers and Operations Research
On stochastic dynamic programming for solving large-scale planning problems under uncertainty
Computers and Operations Research
Discrete lot sizing and scheduling using product decomposition into attributes
Computers and Operations Research
Solving Lot-Sizing Problems on Parallel Identical Machines Using Symmetry-Breaking Constraints
INFORMS Journal on Computing
Polyhedral analysis for the two-item uncapacitated lot-sizing problem with one-way substitution
Discrete Applied Mathematics
A new heuristic method for capacitated multi-level lotsizing problem with backlogging
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
A modelling approach for dynamic and complex capacities in production control systems
BIS'07 Proceedings of the 10th international conference on Business information systems
A polynomial time algorithm for the stochastic uncapacitated lot-sizing problem with backlogging
IPCO'08 Proceedings of the 13th international conference on Integer programming and combinatorial optimization
Stochastic lot-sizing with backlogging: computational complexity analysis
Journal of Global Optimization
MIP formulations and heuristics for two-level production-transportation problems
Computers and Operations Research
On the discrete lot-sizing and scheduling problem with sequence-dependent changeover times
Operations Research Letters
A Polyhedral Study of Multiechelon Lot Sizing with Intermediate Demands
Operations Research
A computational analysis of lower bounds for big bucket production planning problems
Computational Optimization and Applications
Computers and Industrial Engineering
| Hi-index | 0.01 |
In spite of the remarkable improvements in the quality of general purpose mixed-integer programming software, the effective solution of a variety of lot-sizing problems depends crucially on the development of tight formulations for the special problem features occurring in practice.After reviewing some of the basic preprocessing techniques for handling safety stocks and multilevel problems, we discuss a variety of aspects arising particularly in small and large bucket (time period) models such as start-ups, changeovers, minimum batch sizes, choice of one or two set-ups per period, etc. A set of applications is described that contains one or more of these special features, and some indicative computational results are presented. Finally, to show another technique that is useful, a slightly different (supply chain) application is presented, for which the a priori addition of some simple mixed-integer inequalities, based on aggregation, leads to important improvements in the results.