Rolling-horizon lot-sizing when set-up times are sequence-dependent

By A. Clark, S. J. Clark. 2000

152 citations recorded by the source corpus.

The challenging problem of efficient lot sizing on parallel machines with sequence-dependent set-up times is modelled using a new mixed integer programming (MIP) formulation that permits multiple set-ups per planning period. The resulting model is generally too large to solve optimally and, given that it will be used on a rolling horizon basis with imperfect demand forecasts, approximate models that only generate exact schedules for the immediate periods are developed. Both static and rolling horizon snapshot tests are carried out. The approximate models are tested and found to be practical rolling horizon proxies for the exact model, reducing the dimensionality of the problem and allowing for faster solution by MIP and metaheuristic methods. However, for large problems the approximate models can also consume an impractical amount of computing time and so a rapid solution approach is presented to generate schedules by solving a succession of fast MIP models. Tests show that this approach is able to produce good solutions quickly.

Subfields: Computer Networks and Communications, Industrial and Manufacturing Engineering, Management Information Systems

View Paper: https://www.semanticscholar.org/paper/0197afd8b0500967eb3a789eb0838db87e5abca8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Bernardo Almada-Lobo
2. Maria Antónia carravilla
3. Diego Klabjan
4. José Fernando Oliveira

In Industrial and Manufacturing Engineering

1. Ross J. W. James
2. Bernardo Almada-Lobo
3. Maria Antónia carravilla
4. Diego Klabjan
5. José Fernando Oliveira

In Management Information Systems

1. Ross J. W. James
2. Bernardo Almada-Lobo
3. Maria Antónia carravilla
4. Diego Klabjan
5. José Fernando Oliveira

Citations in the corpus

• Neighbourhood search meta-heuristics for capacitated lot-sizing with sequence-dependent setups (2010, background): “Clark and Clark ( 2000 ) develop a mixed-integer programming (MIP) model for this problem on parallel machines that allows for multiple setups (up to a pre-determined number) per planning period.”
• Single machine multi-product capacitated lot sizing with sequence-dependent setups (2007, methodology): “Table 2: Benchmark of models’ complexity Model Binary Continuous Constraints variables variables F1 N2T 4NT NT (2 +N) + 2T Clark and Clark (2000) N2(ST − 1) +N SNT NT (SN + 2S + 2) +1−N Gupta and Magnusson (2005) N2T + 4NT 2NT NT (5 + 3N) + 8T”