Original Research

A Euclidean-based decision model for logistic mobilisation to disaster area

Ayu K. Ferina, Ditdit N. Utama
Journal of Transport and Supply Chain Management | Vol 17 | a963 | DOI: https://doi.org/10.4102/jtscm.v17i0.963 | © 2023 Ayu Kristianty Ferina, Ditdit Nugeraha Utama | This work is licensed under CC Attribution 4.0
Submitted: 27 June 2023 | Published: 18 October 2023

About the author(s)

Ayu K. Ferina, Department of Computer Science, BINUS Graduate Program, Bina Nusantara University, Jakarta, Indonesia
Ditdit N. Utama, Department of Computer Science, BINUS Graduate Program, Bina Nusantara University, Jakarta, Indonesia

Abstract

Background: The fulfilment of the emergency response to the disaster area not only prioritises foods or medicines but also helps in mobilisation of equipment, facilities, and infrastructures in the form of logistics. The suitable warehouses will be able to provide every logistic needed and this will have a positive impact on the government as one of the relief institutions that is responsible for helping the refugees as quickly as possible.

Objectives: The objectives of the study are to determine the logistic needs from disaster area, analyse and evaluate all assets from the 35 warehouses, identify the key indicators to generate the parameter, and to generate several mathematical formulas to be used in the simulation case.

Method: Euclidean-based methodology is applied to calculate every fitness distance as a gap value of each parameter. All stock quantity from 35 warehouses will be the source of the data, with the logistic needs play role as the initial input for the calculation processes.

Results: The logistic needs and the distance resulted in this study became the key indicators to determine the criteria. The study also generates seven equations for the disaster’s case simulation.

Conclusion: To conclude, the outcomes resulted from the simulation indicate that from 35 warehouses alternatives, the fitness gap calculation completed at the 31st warehouse and the public hydrant became the fastest logistic, which completed all demand by two warehouses.

Contribution: The study will be useful for the decision makers as the recommendation and guideline to improve the acceleration of emergency response of the logistic mobilisation from selected and prioritised warehouses.


Keywords

emergency response; warehouse; disaster; logistic; relief; refugees; decision model; Euclidean

JEL Codes

C61: Optimization Techniques • Programming Models • Dynamic Analysis

Sustainable Development Goal

Goal 6: Clean water and sanitation

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