Solving the Public Transportation Problem Using Linear Programming and hybrid PS-ACO Meta-heuristic Method

Bus urban public transport is one of the most considered systems and the buses have received more attention because of their special privileges compared to other systems. In most cities, the bus system is responsible due to the lack of advanced transportation systems such as subways, trams, and light-rail. Due to the positive attributes and advantages of this system, the improvement of their capabilities needs planning and consulting with experts. In this paper, a linear programming model for optimizing the public bus transportation system is proposed to minimize the total cost of setting up the lines, maintenance costs and fuel consumption as well as minimizing the bus arrival times in order to increase the welfare of the passengers. The proposed model is simulated in GAMS software and the sensitivity analysis is performed over the parameters. Due to the time complexity of the proposed model, a hybrid meta-heuristic method based on the Ant Colony Optimization (ACO) and Particle Swarm Intelligence (PSO) name PS-ACO is also developed and simulated in Matlab for solving the proposed model. The computational results show that the fuel cost and distance between stations have the most effect on operational cost, and the time distance between the stations is the most effective parameter on the passenger's welfare. Besides, the number of the stations highly affects the model complexity and solution time.

Article Type:
Research/Original Article
Journal of Transportation Engineering, Volume:11 Issue:2, 2019
353 - 371  
روش‌های دسترسی به متن این مطلب
اشتراک شخصی
در سایت عضو شوید و هزینه اشتراک یک‌ساله سایت به مبلغ 300,000ريال را پرداخت کنید. همزمان با برقراری دوره اشتراک بسته دانلود 100 مطلب نیز برای شما فعال خواهد شد!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی همه کاربران به متن مطالب خریداری نمایند!