Solving a Multi-resource Partial-Ordering Flexible Variant of the Job-Shop Scheduling Problem with Hybrid ASP

Many complex activities in production cycles, such as quality control or fault analysis, require highly experienced specialists to perform various operations on (semi)finished products using different tools. In practical scenarios, the next operation selection is complicated since each expert has only a local view on the entire set of operations to be performed. As a result, decisions made by the specialists are suboptimal and might cause high costs. In this paper, we consider a Multi-resource Partial-ordering Flexible Job-shop Scheduling (MPF-JSS) problem where partially-ordered sequences of operations must be scheduled on multiple required resources, such as tools and specialists. The resources are flexible and can perform one or more operations depending on their properties. We model the problem using Answer Set Programming (ASP), which can efficiently handle time assignments using Difference Logic. Moreover, we suggest two multi-shot solving strategies aiming to identify the time bounds allowing for a solution to the schedule optimization problem. Experiments conducted on a set of instances extracted from a medium-sized semiconductor fault analysis lab indicate that our approach can find schedules for 87 out of 91 considered real-world instances.