GRASP-Based Memetic Algorithm for Multi-period Technician Routing Problem with Mandatory Assigned Tasks and Selective Tasks

This chapter introduces a new variant of the Technician Routing and Scheduling Problem (TRSP) called the Multi-period TRSP with Profits (MPTRSPP), which is crucial for optimizing technician routes in fluid distribution networks. The study is motivated by a real-world application in the water industry, where efficient resource allocation is essential to avoid penalties and maintain service quality. The MPTRSPP model integrates mandatory tasks with fixed days and selective tasks that can be planned over multiple periods, addressing a gap in the existing literature. The proposed solution involves a GRASP-based memetic algorithm, which combines the diversification capabilities of GRASP with the intensification characteristics of a memetic algorithm. The algorithm is validated using real industrial instances, demonstrating significant improvements in intervention rates and priority consideration compared to deterministic heuristics. The study also explores the distribution of task priorities assigned by different algorithms, providing insights into their effectiveness. Overall, the chapter presents a robust approach to tackling complex routing and scheduling problems in the fluid distribution sector, with potential applications in other distribution networks such as electricity and gas.