VGU RESEARCH REPOSITORY
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Title: | A comparison between deep reinforce learning and other optimization methods for VRPTW in Vietnam | Authors: | Tran Thi Cam Tu | Keywords: | Optimization methods;Deep reinforce learning | Issue Date: | 2021 | Abstract: | In logistics business, Vehicle Routing Problem is a very famous problem in the world which was first described by Dantzig and Ramser in 1959. And the solution for this problem is to define the most optimized route in which it can cover the most delivery points, in the shortest time frame, and has the minimized cost. In practical, it is so difficult to define such optimal route like that when there are lots of unexpected issues happen such as customer change the received address, traffic jams, bad weather which increase the delivery cost so much and influence on customers’ experiment. Since 1959, several researchers have identified different solutions to solve the optimal problems. Many algorithms have been investigated and applied to solve the problem. Among them, we can mention on Ant colony optimization algorithm, Genetic algorithm and so on. Based on the practical need, and the appearance of deep learning. A new approach is introduced to solve the Vehicle Routine Problem named Reinforce Learning method. However, as prior claims, Vehicle Routine Problem is a complex topic in which the optimized route depend mostly on the number of factors we choose in the problems. In the thesis scope and the situation of Vietnam, there are some main factors and constraints will be chosen to solve the problems. Some parameters are customer will receive their order within a time window, the loads is not exceeded the capacity of the vehicles, multiple customers can be served with a limited number vehicles |
URI(1): | https://epub.vgu.edu.vn/handle/dlibvgu/1279 |
Appears in Collections: | Business Information Systems (BIS) Business Information Systems (BIS) |
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