EURO 2024 Copenhagen
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4050. Batching and scheduling with OptalCP

Invited abstract in session TA-60: Project Management, stream Project Management and Scheduling.

Tuesday, 8:30-10:00
Room: S09 (building: 101)

Authors (first author is the speaker)

1. Diego Olivier Fernandez Pons
CoEnzyme

Abstract

In production optimization for manufacturing, directly scheduling the production lines to fulfil the make-to-order, make-to-stock and inventory needs is usually too computationally demanding. Commonly, the problem is divided into a batching phase that creates production batches and pre-assigns them to orders, and a scheduling phase that assigns the batches to machines while minimizing completion time.

This decomposition is usually difficult to adjust, as a too tight batching phase may result in a solution that is far from optimality or even make the scheduling sub-problem infeasible, when a too loose one will result in a scheduling problem that is too hard.

Scheduling engines have gained popularity for the scheduling phase due to their ability to quickly return solutions of high quality while supporting a large variety of scheduling constraints, when the batching phase is usually done with mixed-integer linear programming.

OptalCP is a state-of-the-art scheduling engine in the lineage of IBM ILOG CP Optimizer, that first started providing a MIP-like experience for scheduling engines (lower bounds, model & run). We have extended it to also solve batching and scheduling problems without decomposition.

Keywords

Status: accepted

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