การประยุกต์ใช้วิธีการหาค่าที่เหมาะสมที่สุด แบบฝูงอนุภาคในการจัดตารางเวลารถไฟ - กรณ์พงษ์ อึงสถิตย์ถาวร (เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่, 2020)
This research aims to solve a Train Scheduling Timetabling Problem of Northern path in Thailand by rescheduling arrival and departure time of all trains to find the minimum travelling time within a reasonable solving time while satisfying all constraints. Research methodology consists of four phases. The first phase is analyze and create a running time in each rail section for all train types from Bangkok Station to Chiang Mai Station, including a branch rail to Sawankalok Station, and define a section’s velocity limit which consist of 260 sections. Following that, the mathematical model was created and those equations and numbers were turns into the expression of Lingo language to find a optimal solution, but this mathematical model is capable of small cases. The next phase was to apply the Particle Swarm Optimization technique to rescheduling timetabling in a larger problem scale and coding a whole algorithm by using the VC# program. Afterward, a simulation model was built by using Arena program for simulation of unstable factors, also including a probability of locomotive break down, and it’s repairing time as well as uncertain factors regarding stop time at station sections along the route. The simulation result showed that mean time for each trains which using the Particle Swarm Optimization technique is 353.86 minutes when compared with average times from present timetables was 398.20 minutes, which was reduced 11.14%.