Minimizing setups and waste when printing labels of consumer goods

A real-world planning problem of a printing company is presented where different sorts of a consumer goods’ label are printed on a roll of paper with sufficient length. The printer utilizes a printing plate to always print several labels of same size and shape (but possibly different imprint) in parallel on adjacent lanes of the paper. It can be decided which sort is printed on which (lane of a) plate and how long the printer runs using a single plate. A sort can be assigned to several lanes of the same plate, but not to several plates. Designing a plate and installing it on the printer incurs fixed setup costs. If more labels are produced than actually needed, each surplus label is assumed to be “scrap”. Since demand for the different sorts may be heterogeneous and since the number of sorts is usually much higher than the number of lanes, the problem is to build “printing blocks”, i.e., to decide how many and which plates to design and how long to run the printer with a certain plate so that customer demand is satisfied with minimum costs for setups and scrap. This industrial application is modeled as an extension of a so-called job splitting problem which is solved exactly and by various decomposition heuristics, partly basing on dynamic programming. Numerical tests compare both approaches with further straightforward heuristics and demonstrate the benefits of decomposition and dynamic programming for large problem instances.

Flexible Job Shop Scheduling Problem with Sequence Dependent Setup Time and Job Splitting: Hospital Catering Case Study

This paper aims to study a real case of an optimization problem derived from a hospital supply chain. The present work focuses on developing operational decision support models and algorithms for production process scheduling in hospital catering. The addressed production system is considered as a flexible job shop system. The objective is to minimize the total flow time. A novel mathematical model and two metaheuristics for the production scheduling of multi-product and multi-stage food processes are developed. These methods have proven their effectiveness for the scheduling of operations of the food production processes and allowed significant improvements in the performance of the studied production system.