Intelligent Scheduling and Routing of a Heterogenous Fleet of Automated Guided Vehicles (AGVs) in a Production Environment with Partial Recharge

Abstract

Use of Automated Guided Vehicles (AGVs) for material handling purposes has become increasingly popular. They introduce flexibility to the system by increasing the speed responsiveness and freight capacity as well as enabling increased productivity safety efficient resource utilization and reducing costs. These advantages can be realized by intelligent assignment of AGVs to jobs and routing of AGVs to meet production plans. We look at the problem of scheduling and routing of a heterogenous fleet of AGVs consisting of different types based on purpose of use freight and battery charge capacity used for handling transfer jobs in a production environment. The objective is to optimize the schedules and routes of AGVs by minimizing the penalty cost for the late delivery of a parts and energy consumption of the vehicles. To this end a novel mixed integer linear programming model for a heterogenous fleet of AGVs along with charging and energy consumption is proposed where partial recharging is allowed. Proposed model is validated and verified with a test case using IBM OPL CPLEX and results are provided.