Engineering and Technology Horizons | 2026
Authors: Pakawanich P.
DOI: 10.55003/ETH.430101
Journal: Engineering and Technology Horizons
Year: 2026
Publisher: King Mongkut's Institute of Technology Ladkrabang
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
This study develops a Hybrid Multi–Objective Simulated Annealing (HMOSA) framework for solving the Multi–Objective Capacitated Vehicle Routing Problem in Thailand’s School Milk Program, where balancing efficiency and fairness is essential due to the manual unloading tasks performed by each delivery team. The model minimizes total travel distance and workload imbalance, quantified by the standard deviation of vehicle loads to better capture physical handling effort. The proposed HMOSA introduces two novel mechanisms: i) warm–start initialization using extreme seed solutions generated from Single–Objective SA (SOSA) and Weighted–Sum SA (WSSA), and ii) a guided neighborhood mechanism that selects promising neighbors using weighted scores to enhance search efficiency and diversity. These contributions improve convergence stability without relying on complex parameter tuning. Computational experiments on 10, 30, and 51–customer instances demonstrate that HMOSA consistently outperforms conventional MOSA and SA, and provides superior Pareto–front quality compared with Non-dominated Sorting Genetic Algorithm II NSGA–II. Performance was assessed using two widely adopted indicators: hypervolume (HV) for solution diversity and inverted generational distance (IGD) for convergence reliability. In the real–world 51–school case, small increases in total distance resulted in substantial improvements in workload equity, offering actionable compromise solutions between distance and fairness. Overall, HMOSA embeds fairness into routing decisions while maintaining scalability and robustness, serving as a practical decision–support tool for real routing applications where routing efficiency and equitable workload distribution are both essential. © 2026, King Mongkut's Institute of Technology Ladkrabang. All rights reserved.
Capacitated vehicle routing problem; Hybrid simulated annealing; Multi–objective; workload balance