Optimization of Truck and Driver Scheduling Using Simulated Annealing

Abstract

Truck and driver scheduling in multi-plant heavy goods distribution is a complex problem due to geographically distributed customer sites and plants, truck conditions, and working and resting hour constraints. Moreover, we need to satisfy conflicting objectives such as maximizing order coverage and minimizing of overall costs. We propose an automated truck and driver scheduling solution which consists of a rule checker and a scheduler. Rule checker enforces constraints and conditions such as driver and truck availability, delivery time constraints, and operating and resting hours. A scheduler that uses simulated annealing is proposed to cover as many orders as possible while minimizing the overall cost. The utility of the proposed solution is tested using a workload derived from a real-world bulk-cement distribution company. The results show good coverage of orders where the coverage increased by more than 10% compared to manual scheduling while minimizing the total cost by 35%, as well as enhancing the customer satisfaction and the safety of drivers.