A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises

Mishra, Bhupesh Kumar; Dahal, Keshav; Pervez, Zeeshan; Bhattarai, Suyesh

Abstract

In a disaster scenario, relief items distribution is required as early as possible for the disaster victims to reduce the associated risks. For the distribution tasks, an effective and efficient relief items distribution model is essential to generate relief items distribution schedules to minimise the impact of disaster to the disaster victims. However, developing efficient distribution schedules is challenging as the relief items distribution problem has multiple objectives to look after where the objectives are mostly contradictorily creating a barrier to simultaneous optimisation of each objective. Also, the relief items distribution model has added complexity with the consideration of multiple supply points having heterogeneous and limited vehicles with varying capacity, cost and time. In this paper, multi-objective evolutionary optimisation with the greedy heuristic search has been applied for the generation of relief items distribution schedules under heterogeneous vehicles condition at supply points. The evolutionary algorithm generates the disaster region distribution sequence by applying a global greedy heuristic search along with a local search that finds the efficient assignment of heterogeneous vehicles for the distribution. This multi-objective evolutionary approach provides Pareto optimal solutions that decision-makers can apply to generate effective distribution schedules to optimise the distribution time and vehicles’ operational cost. In addition, this optimisation process also incorporated the minimisation of unmet relief items demand at the disaster regions. The optimised distribution schedules with the proposed approach are compared with the single-objective optimisation, weighted single-objective optimisation and greedy multi-objective optimisation approaches. The comparative results showed that the proposed multi-objective evolutionary approach is an efficient alternative for finding the distribution schedules with optimisation of distribution time and operational cost for the relief items distribution with heterogeneous vehicles in humanitarian crisis.

Citation

Mishra, B. K., Dahal, K., Pervez, Z., & Bhattarai, S. (2022). A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises. Decision Analytics Journal, 5, Article 100128. https://doi.org/10.1016/j.dajour.2022.100128

• Journal Article Type: Article
• Acceptance Date: Sep 11, 2022
• Online Publication Date: Sep 15, 2022
• Publication Date: Dec 1, 2022
• Deposit Date: Jul 1, 2024
• Publicly Available Date: Jul 2, 2024
• Journal: Decision Analytics Journal
• Electronic ISSN: 2772-6622
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Article Number: 100128
• DOI: https://doi.org/10.1016/j.dajour.2022.100128
• Keywords: Multi-objective scheduling; Disaster; Evolutionary algorithm; Optimisation; Relief items distribution; Heterogeneous vehicles; Humanitarian Crisis
• Public URL: https://hull-repository.worktribe.com/output/4730497