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

Mishra, Bhupesh ORCID: 0000-0003-3430-8989, Dahal, Keshaw, Pervez, Zeeshan and Bhattari, Suyesh (2022) A multi-objective evolutionary optimisation model for heterogeneous vehicles routing and relief items scheduling in humanitarian crises. Decision Analytics Journal, 5. Art 100128. doi:10.1016/j.dajour.2022.100128

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11583 Mishra, Dahal, Zeeshan and Bhattari (2022) A multi-Objective Evolutionary Optimisation Model.pdf - Accepted Version
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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 to generated relief items distribution schedules is essential 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 that optimise the distribution time and vehicles’ operational cost. In addition, this optimisation 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.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Multi-Objective scheduling; Disaster; In Humanitarian Crises; Evolutionary Algorithm; Optimisation; Relief Items; Distribution; Heterogeneous Vehicles
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Schools and Research Institutes > School of Creative Arts
Research Priority Areas: Applied Business & Technology
Depositing User: Kate Greenaway
Date Deposited: 16 Sep 2022 16:01
Last Modified: 28 Sep 2023 12:18
URI: https://eprints.glos.ac.uk/id/eprint/11583

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