Underground mine scheduling of mobile machines using Constraint Programming and Large Neighborhood Search. (November 2020) - Åstrand, Max
Highlights: Constraint Programming is used for scheduling mobile machines in an underground mine. Domain-specific neighborhoods are introduced and used in Large Neighborhood Search. Models are evaluated on instances derived from real-world data. The proposed method quickly finds high-quality schedules. Abstract: Manual short-term scheduling in underground mines is a time-consuming and error-prone activity. In this work, we present a Constraint Programming approach capable of automating the short-term scheduling process in a cut-and-fill mine. The approach extends previous work by accounting for fleet travel times, and thus captures an important aspect of the real-world machine scheduling problem. We introduce two models: one that directly solves the original interruptible scheduling problem, and one that is based on solving a related uninterruptible scheduling problem and transforming its solution back to the original domain. Large Neighborhood Search is also employed with a domain-specific neighborhood definition that helps to find high-quality schedules faster. Problem instances derived from an operational mine are used to demonstrate the efficacy of our approach.