Inventory lot-sizing with supplier selection
Computers and Operations Research
Workforce planning in a lotsizing mail processing problem
Computers and Operations Research
Comparative approaches to equipment scheduling in high volume factories
Computers and Operations Research
A bilinear reduction based algorithm for solving capacitated multi-item dynamic pricing problems
Computers and Operations Research
Integrated production planning and preventive maintenance in deteriorating production systems
Information Sciences: an International Journal
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
Comparative approaches to equipment scheduling in high volume factories
Computers and Operations Research
On the discrete lot-sizing and scheduling problem with sequence-dependent changeover times
Operations Research Letters
Lot sizing with inventory gains
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
Review: Operations research in solid waste management: A survey of strategic and tactical issues
Computers and Operations Research
Hi-index | 0.01 |
Based on research on the polyhedral structure of lot-sizing models over the last 20 years, we claim that there is a nontrivial fraction of practical lot-sizing problems that can now be solved by nonspecialists just by taking an appropriate a priori reformulation of the problem, and then feeding the resulting formulation into a commercial mixed-integer programming solver.This claim uses the fact that many multi-item problems decompose naturally into a set of single-item problems with linking constraints, and that there is now a large body of knowledge about single-item problems. To put this knowledge to use, we propose a classification of lot-sizing problems (in large part single-item) and then indicate in a set of tables, what is known about a particular problem class and how useful it might be. Specifically, we indicate for each class (i) whether a tight extended formulation is known, and its size; (ii) whether one or more families of valid inequalities are known defining the convex hull of solutions, and the complexity of the corresponding separation algorithms; and (iii) the complexity of the corresponding optimization algorithms (which would be useful if a column generation or Lagrangian relaxation approach was envisaged).Three distinct multi-item lot-sizing instances are then presented to demonstrate the approach, and comparative computational results are presented. Finally, we also use the classification to point out what appear to be some of the important open questions and challenges.