Conflict detection in Task Heterogeneous Information Networks

Abstract

Task scheduling problems are involved in various fields, such as personal travel planning, UAV group path planning, intelligent furniture task scheduling and so on. As most of these task scheduling problems are subject to constraints of time, space and resource, conflicts often arise. However, the existing methods are typically limited to specific areas or geared to meet one or two types of constraints. As a result, they are unable to solve all conflicts systematically. This paper proposes a Task Heterogeneous Information Network (THIN) to model scheduling tasks and constraints comprehensively. Then, by dynamically exploring and converting Task Heterogeneous Information Networks, a series of algorithms are designed to detect and resolve all types of conflicts. Finally, conflict-free task plans are produced as outputs. Experiments have been conducted on datasets of different sizes, and the results show that our methods are effective.