The dynamic lot-sizing problem with startup and reservation costs
Operations Research
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Computers and Industrial Engineering
A user interactive heuristic procedure for solving the multiple product cycling problem
Computers and Operations Research
Lot-Sizing with Start-Up Times
Management Science
Production Planning by Mixed Integer Programming (Springer Series in Operations Research and Financial Engineering)
Integrated pulp and paper mill planning and scheduling
Computers and Industrial Engineering
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We address the short-term production planning and scheduling problem coming from the glass container industry. A furnace melts the glass that is distributed to a set of parallel molding machines. Both furnace and machine idleness are not allowed. The resulting multi-machine multi-item continuous setup lotsizing problem with a common resource has sequence-dependent setup times and costs. Production losses are penalized in the objective function since we deal with a capital intensive industry. We present two mixed integer programming formulations for this problem, which are reduced to a network flow type problem. The two formulations are improved by adding valid inequalities that lead to good lower bounds. We rely on a Lagrangian decomposition based heuristic for generating good feasible solutions. We report computational experiments for randomly generated instances and for real-life data on the aforementioned problem, as well as on a discrete lotsizing and scheduling version.