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dc.contributor.authorSoenandi, IA-
dc.contributor.authorJuan, Y-
dc.contributor.authorBudi, M-
dc.date.accessioned2019-03-18T03:51:09Z-
dc.date.available2019-03-18T03:51:09Z-
dc.date.issued2018-11-19-
dc.identifier.issn1757-899X-
dc.identifier.urihttp://repository.ukrida.ac.id:80/handle/123456789/51-
dc.description.abstractRecently, increasing usage of marine products is creating new challenges for businesses of marine products in term of transportations that used to carry the marine products like seafood to the main warehouse. This can be a problem if the carrier fleet is limited, and there are time constraints in terms of the freshness of the marine product. there are many ways to solve this problem, including the optimization of routing vehicle. In this study, this strategy is to implement in the marine product business in Indonesia with such an expected arrangement of the company to optimize routing problem in transportation with time and capacity windows. Until now, the company has not used the scientific method to manage the routing of their vehicle from warehouse to the location of marine products source. This study will solve a stochastic Vehicle Routing Problems (VRP) with time and capacity windows by using the comparison of six methods and looking the best results for the optimization, in this research, we compared the optimization with another method such as branch and bound, dynamic programming and Ant Colony Optimization (ACO). Finally, we get the best result after running ACO algorithm with existing travel time data. With ACO algorithm was able to reduce vehicle travel time by 3189.65 minutes, which is about 23% less than existing and based on consideration of the constraints of time within 2days (including rest time for the driver) using 28 tons capacity of truck and the companies need two units of vehicles for transportation.en_US
dc.language.isoen_USen_US
dc.subjectOptimizationen_US
dc.subjectIndonesia Marine producten_US
dc.subjectStochastic Vehicle Routing problem with Time Windows and Capacity Windowsen_US
dc.subjectAnt Colony Optimizationen_US
dc.titleOptimization for Routing Vehicles of Seafood Product Transportationen_US
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