Abousaeidi, M. and Fauzi, R. and Muhamad, R. (2016) Geographic Information System (GIS) modeling approach to determine the fastest delivery routes. Saudi Journal of Biological Sciences, 23 (5). pp. 555-564. ISSN 1319-562X, DOI https://doi.org/10.1016/j.sjbs.2015.06.004.
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Abstract
This study involves the adoption of the Geographic Information System (GIS) modeling approach to determine the quickest routes for fresh vegetable delivery. During transport, fresh vegetables mainly deteriorate on account of temperature and delivery time. Nonetheless, little attention has been directed to transportation issues in most areas within Kuala Lumpur. In addition, perishable food normally has a short shelf life, thus timely delivery significantly affects delivery costs. Therefore, selecting efficient routes would consequently reduce the total transportation costs. The regression model is applied in this study to determine the parameters that affect route selection with respect to the fastest delivery of fresh vegetables. For the purpose of this research, ArcGIS software with network analyst extension is adopted to solve the problem of complex networks. The final output of this research is a map of quickest routes with the best delivery times based on all variables. The variables tested from regression analysis are the most effective parameters to make the flow of road networks slower. The objective is to improve the delivery services by achieving the least drive time. The main findings of this research are that Land use such as residential area and population as variables are the effective parameters on drive time.
Item Type: | Article |
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Funders: | UNSPECIFIED |
Uncontrolled Keywords: | Geographic Information System; Hypermarkets; Network analysis; Quickest routes; Regression model |
Subjects: | G Geography. Anthropology. Recreation > G Geography (General) H Social Sciences > H Social Sciences (General) |
Divisions: | Faculty of Arts and Social Sciences Faculty of Business and Economics |
Depositing User: | Ms. Juhaida Abd Rahim |
Date Deposited: | 20 Oct 2017 02:45 |
Last Modified: | 20 Oct 2017 02:45 |
URI: | http://eprints.um.edu.my/id/eprint/18020 |
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