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Epidemic-Logistics Network Considering Time Windows and Service Level

In this chapter, we present two optimization models for optimizing the epidemic-logistics network. In the first one, we formulate the problem of emergency materials distribution with time windows to be a multiple traveling salesman problem. Knowledge of graph theory is used to transform the MTSP to...

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Autores principales: Liu, Ming, Cao, Jie, Liang, Jing, Chen, MingJun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120198/
http://dx.doi.org/10.1007/978-981-13-9353-2_13
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author Liu, Ming
Cao, Jie
Liang, Jing
Chen, MingJun
author_facet Liu, Ming
Cao, Jie
Liang, Jing
Chen, MingJun
author_sort Liu, Ming
collection PubMed
description In this chapter, we present two optimization models for optimizing the epidemic-logistics network. In the first one, we formulate the problem of emergency materials distribution with time windows to be a multiple traveling salesman problem. Knowledge of graph theory is used to transform the MTSP to be a TSP, then such TSP route is analyzed and proved to be the optimal Hamilton route theoretically. Besides, a new hybrid genetic algorithm is designed for solving the problem. In the second one, we propose an improved location-allocation model with an emphasis on maximizing the emergency service level. We formulate the problem to be a mixed-integer nonlinear programming model and develop an effective algorithm to solve the model. In this chapter, we present two optimization models for optimizing the epidemic-logistics network. In the first one, we formulate the problem of emergency materials distribution with time windows to be a multiple traveling salesman problem. Knowledge of graph theory is used to transform the MTSP to be a TSP, then such TSP route is analyzed and proved to be the optimal Hamilton route theoretically. Besides, a new hybrid genetic algorithm is designed for solving the problem. In the second one, we propose an improved location-allocation model with an emphasis on maximizing the emergency service level. We formulate the problem to be a mixed-integer nonlinear programming model and develop an effective algorithm to solve the model.
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spelling pubmed-71201982020-04-06 Epidemic-Logistics Network Considering Time Windows and Service Level Liu, Ming Cao, Jie Liang, Jing Chen, MingJun Epidemic-logistics Modeling: A New Perspective on Operations Research Article In this chapter, we present two optimization models for optimizing the epidemic-logistics network. In the first one, we formulate the problem of emergency materials distribution with time windows to be a multiple traveling salesman problem. Knowledge of graph theory is used to transform the MTSP to be a TSP, then such TSP route is analyzed and proved to be the optimal Hamilton route theoretically. Besides, a new hybrid genetic algorithm is designed for solving the problem. In the second one, we propose an improved location-allocation model with an emphasis on maximizing the emergency service level. We formulate the problem to be a mixed-integer nonlinear programming model and develop an effective algorithm to solve the model. In this chapter, we present two optimization models for optimizing the epidemic-logistics network. In the first one, we formulate the problem of emergency materials distribution with time windows to be a multiple traveling salesman problem. Knowledge of graph theory is used to transform the MTSP to be a TSP, then such TSP route is analyzed and proved to be the optimal Hamilton route theoretically. Besides, a new hybrid genetic algorithm is designed for solving the problem. In the second one, we propose an improved location-allocation model with an emphasis on maximizing the emergency service level. We formulate the problem to be a mixed-integer nonlinear programming model and develop an effective algorithm to solve the model. 2019-10-04 /pmc/articles/PMC7120198/ http://dx.doi.org/10.1007/978-981-13-9353-2_13 Text en © Science Press and Springer Nature Singapore Pte Ltd. 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Liu, Ming
Cao, Jie
Liang, Jing
Chen, MingJun
Epidemic-Logistics Network Considering Time Windows and Service Level
title Epidemic-Logistics Network Considering Time Windows and Service Level
title_full Epidemic-Logistics Network Considering Time Windows and Service Level
title_fullStr Epidemic-Logistics Network Considering Time Windows and Service Level
title_full_unstemmed Epidemic-Logistics Network Considering Time Windows and Service Level
title_short Epidemic-Logistics Network Considering Time Windows and Service Level
title_sort epidemic-logistics network considering time windows and service level
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120198/
http://dx.doi.org/10.1007/978-981-13-9353-2_13
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