An Optimization Method For Integrated Yard Crane And Truck Scheduling Using Genetic Algorithm And Simulation: A Case Of Tan Cang Cat Lai Port

Abstract

With the development of global integration, global trade makes it urgent for every country to develop port and terminal infrastructure and logistics services. In ports and terminals, transporting vehicles like yard cranes and yard trucks contribute greatly to smooth flow of the goods and overall operation. This thesis has taken this problem into consideration and come up with an optimized scheduling solution to minimize average container processing time by applying meta-heuristic called Genetics Algorithms. A simulation model is then developed in ARENA to test whether the suggested solution is applicable in stochastic environments and make a comparison with several basic rules like FIFO, Smallest Distance, Random. The results show that Genetics Algorithm performs very well in scheduling and optimization but does not bring the same effect when comparing with other method in an environment full of randomness. The problem of data integration between Programming tools like Python and ARENA remains for future investigation