Efficient Online Scheduling and Routing for Automated Guided Vehicles In Loop-Based Graphs

TL;DR

This work proposes a loop-based algorithm that solves the online, conflict-free scheduling and routing problem for AGVs with any capacity and ordered jobs in loop-based graphs and experimentally shows that this algorithm either outperforms the other algorithms or gets an equally good solution in less computing time.

Abstract

Automated guided vehicles (AGVs) are widely used in various industries, and scheduling and routing them in a conflict-free manner is crucial to their efficient operation. We propose a loop-based algorithm that solves the online, conflict-free scheduling and routing problem for AGVs with any capacity and ordered jobs in loop-based graphs. The proposed algorithm is compared against an exact method, a greedy heuristic and a metaheuristic. We experimentally show, using theoretical and real instances on a model representing a real manufacturing plant, that this algorithm either outperforms the other algorithms or gets an equally good solution in less computing time.

Figures (6)

• Figure 1: A directed graph representing the general layout of a manufacturing plant that mainly consists of loops and that has a single stockroom marked S. All nodes have a directed edge connecting that node to itself, which is not drawn.
• Figure 2: The simplified directed graph based on a map of a real facility and historical job-data.
• Figure 3: Two graphs depicting conflicts that arise when unmerging nodes.
• Figure 4: MCT in minutes for different instances with a given job density and a job window of 20 jobs. These instances were made using the historical data.
• Figure 5: ASU for different instances with a given job density and a job window of 20 jobs. These instances were made using the historical data.