Abstract:

In this project, we investigate the solution of automated vehicle routing by K-means algorithm and vehicle routing decision support system for a real time case study of Iron Mountain’s logistics operations. By defining and evaluating the performance measurements on service level and vehicle utilization of Iron Mountain’s logistics operations, systematic approach for vehicle scheduling through literature review, data analysis and evaluation, solution approach, cost analysis. It is found that Iron Mountain’s logistics operation performance is unsatisfactory, low utilization of vehicles, low fulfilment, unbalance loading quantity, unoptimized travelling time. To investigate the optimization of logistics operation of in-house and outsourcing strategies. K-means and Track-pod were used when solving the automated vehicle routing, which is easy to implement even with free-trial, enhancing the utilization of vehicle and fulfilment of time requirement under operation of in-house logistics. As the result of cost analysis, stand with the advantage of in-house logistics after replanning the routes. Comparing outsourcing (SF Express) and crowdsourcing (GOGOVAN) with in-house logistics, the result shown in-house logistics operation takes advantage in both management aspect and cost consideration under business as usual scenario.