Continuous-time model for multi-product scheduling in production

TL;DR

This paper develops a continuous-time mixed integer linear programming model for multi-product scheduling involving multi-machine technologies with sequence-dependent setup times, tested on randomly generated instances.

Contribution

It introduces a novel MILP formulation for multi-product scheduling with multi-machine technologies and sequence-dependent setup times, including a special case with triangle inequality.

Findings

Models are experimentally validated on random instances.

The approach effectively captures complex scheduling constraints.

Results demonstrate the model's applicability to real-world scenarios.

Abstract

We consider a problem of multi-product scheduling in production. Each product can be produced by a family of alternative multi-machine technologies. Multi-machine technologies require more than one machine at the same time. A sequence dependent setup time is needed between different technologies. We formulate a mixed integer linear programming model for the general case of the problem and for the case, when the setup times satisfy the triangle inequality. The proposed models are experimentally tested on randomly generated instances.