Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization

Coronavirus disease (COVID-19) has spread for over a year and affected many aspects, including the food supply chain. One of the ways COVID-19 has impacted the food supply chain is the food production capacity reduction. It is necessary to develop the optimum food supply chain strategy by determinin...

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Autores principales:	Audi Luqmanul Hakim Achmad, Diah Chaerani, Tomy Perdana
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Food supply chain COVID-19 Robust Optimization Agent-Based Modelling Uncertainty Simulation Science (General) Q1-390 Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/13d6d33a29c34959930f58cdf08c5152
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spelling	oai:doaj.org-article:13d6d33a29c34959930f58cdf08c51522021-12-02T05:03:16ZDesigning a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization2405-844010.1016/j.heliyon.2021.e08448https://doaj.org/article/13d6d33a29c34959930f58cdf08c51522021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2405844021025512https://doaj.org/toc/2405-8440Coronavirus disease (COVID-19) has spread for over a year and affected many aspects, including the food supply chain. One of the ways COVID-19 has impacted the food supply chain is the food production capacity reduction. It is necessary to develop the optimum food supply chain strategy by determining the optimum food hub location and food network to maintain food security which robust against disruptions and uncertainties. In this study, Robust Optimization (RO) is applied to handle the uncertainties. Nevertheless, the actual uncertain data might be hard to be collected or even unavailable at the moment. Therefore, an innovative framework is proposed to integrate RO with Agent-Based Modelling (ABM). ABM is used to simulate the upstream actor of the food supply chain and predict the uncertain food production capacity, which RO later handles. Particularly, this study focused on rice supply chain. The result shows that the framework is able to handle the uncertain rice supply chain problem, in which the actual uncertain data might be unavailable, and give the robust optimum food hub location and food network. The food hub location and food network are obtained by solving the Robust Counterpart (RC) model with respect to the uncertainty set obtained from the ABM simulation result.Audi Luqmanul Hakim AchmadDiah ChaeraniTomy PerdanaElsevierarticleFood supply chainCOVID-19Robust OptimizationAgent-Based ModellingUncertaintySimulationScience (General)Q1-390Social sciences (General)H1-99ENHeliyon, Vol 7, Iss 11, Pp e08448- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Food supply chain COVID-19 Robust Optimization Agent-Based Modelling Uncertainty Simulation Science (General) Q1-390 Social sciences (General) H1-99
spellingShingle	Food supply chain COVID-19 Robust Optimization Agent-Based Modelling Uncertainty Simulation Science (General) Q1-390 Social sciences (General) H1-99 Audi Luqmanul Hakim Achmad Diah Chaerani Tomy Perdana Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
description	Coronavirus disease (COVID-19) has spread for over a year and affected many aspects, including the food supply chain. One of the ways COVID-19 has impacted the food supply chain is the food production capacity reduction. It is necessary to develop the optimum food supply chain strategy by determining the optimum food hub location and food network to maintain food security which robust against disruptions and uncertainties. In this study, Robust Optimization (RO) is applied to handle the uncertainties. Nevertheless, the actual uncertain data might be hard to be collected or even unavailable at the moment. Therefore, an innovative framework is proposed to integrate RO with Agent-Based Modelling (ABM). ABM is used to simulate the upstream actor of the food supply chain and predict the uncertain food production capacity, which RO later handles. Particularly, this study focused on rice supply chain. The result shows that the framework is able to handle the uncertain rice supply chain problem, in which the actual uncertain data might be unavailable, and give the robust optimum food hub location and food network. The food hub location and food network are obtained by solving the Robust Counterpart (RC) model with respect to the uncertainty set obtained from the ABM simulation result.
format	article
author	Audi Luqmanul Hakim Achmad Diah Chaerani Tomy Perdana
author_facet	Audi Luqmanul Hakim Achmad Diah Chaerani Tomy Perdana
author_sort	Audi Luqmanul Hakim Achmad
title	Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
title_short	Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
title_full	Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
title_fullStr	Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
title_full_unstemmed	Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization
title_sort	designing a food supply chain strategy during covid-19 pandemic using an integrated agent-based modelling and robust optimization
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/13d6d33a29c34959930f58cdf08c5152
work_keys_str_mv	AT audiluqmanulhakimachmad designingafoodsupplychainstrategyduringcovid19pandemicusinganintegratedagentbasedmodellingandrobustoptimization AT diahchaerani designingafoodsupplychainstrategyduringcovid19pandemicusinganintegratedagentbasedmodellingandrobustoptimization AT tomyperdana designingafoodsupplychainstrategyduringcovid19pandemicusinganintegratedagentbasedmodellingandrobustoptimization
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Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization

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