2024/03/21 by Yuji Zou, Zou, Yuji, Jin‐Kao Hao +3 · 2 citations
Computer Science · Engineering · #Discrete Mathematics (cs.DM) #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #IPv6, Mobility, Handover, Networks, Security #Mobile Agent-Based Network Management #Neural and Evolutionary Computing (cs.NE)
paper · pdf · doi:10.48550/arxiv.2403.14405
openalex publication_date 2024/03/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The latency location routing problem integrates the facility location problem and the multi-depot cumulative capacitated vehicle routing problem. This problem involves making simultaneous decisions about depot locations and vehicle routes to serve customers while aiming to minimize the sum of waiting (arriving) times for all customers. To address this computationally challenging problem, we propose a reinforcement learning guided hybrid evolutionary algorithm following the framework of the memetic algorithm. The proposed algorithm relies on a diversity-enhanced multi-parent edge assembly crossover to build promising offspring and a reinforcement learning guided variable neighborhood descent to determine the exploration order of multiple neighborhoods. Additionally, strategic oscillation is used to achieve a balanced exploration of both feasible and infeasible solutions. The competitiveness of the algorithm against state-of-the-art methods is demonstrated by experimental results on the three sets of 76 popular instances, including 51 improved best solutions (new upper bounds) for the 59 instances with unknown optima and equal best results for the remaining instances. We also conduct additional experiments to shed light on the key components of the algorithm.