Reducing Energy Consumption in Electronic Component Manufacturing through Large Neighborhood Search

Abstract

Amidst the ongoing climate crisis, there is a pressing need to reduce energy consumption - especially in industrial settings, as recognized by the United Nations Sustainability Goals (in particular, 9 and 12). To mitigate energy usage in production, strategically grouping compatible jobs and processing them together in batches, as captured by batch scheduling problems, is often beneficial. The Oven Scheduling Problem (OSP), is an NP-hard real-world parallel batch scheduling problem that arises in the electronic component industry. The goal of the OSP is to schedule jobs on ovens while minimizing total oven operating time, job tardiness, and setup costs. To reduce oven runtime, compatible jobs can be processed simultaneously in batches. The schedule must respect oven eligibility and availability, job release dates, setup times between batches, and oven capacity constraints.We propose and fine-tune a Large Neighborhood Search (LNS) algorithm that uses three different destroy operators and a repair operator based on an exact method (a Constraint Programming model). Our findings demonstrate that LNS significantly enhances the solution quality for many large instances compared to existing exact methods from the literature. Furthermore, we develop a user-friendly dashboard to facilitate decision-makers in the navigation of the optimization tool.