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http://dx.doi.org/10.11627/jkise.2018.41.4.138

Logistics Allocation and Monitoring System based on Map and GPS Information  

Park, Chulsoon (School of Industrial Engineering and Naval Architecture, Changwon National University)
Bajracharya, Larsson (Dept of Information & Communication Engineering, Changwon National University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.41, no.4, 2018 , pp. 138-145 More about this Journal
Abstract
In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.
Keywords
Multiple Pickup and Delivery; Optimization Model; Logistics Allocation and Monitoring; Time Windows;
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