Hagni Wijayanti, Fajar Delli Wihartiko, Fitria Virgantari

Judul	:	Sensitivity Analysis Model Bus Timetabling Problem by Considering Passenger Ease
Abstrak	:	Abstract: The optimal Model Bus Timetabling Problem (MBTP) is a simplification of bus scheduling cases where a bus departure schedule with the optimal number of trips will be searched. The optimal number of trips is defined by maximizing the profit function of the bus by considering constraints such as the availability of buses, the executing officers, the number of passengers and the travel time. This model was developed by adding the constraints of ease of passengers in remembering the schedule. The model is then modified and completed using the branch and bound algorithm. The result of the sensitivity analysis to the model shows that the addition of bus or employee by the manager will not be directly proportional to the addition of passengers. So the addition of buses and employees is done when passengers increase. In addition, the addition of constraints ease passengers in reading the time table will make the increase in corporate profits with the consequences of decreased levels of passenger comfort. If the company chooses to improve the comfort of passengers it will affect the increase of the company's operational costs.
Tahun	:	2019	Media Publikasi	:	Jurnal Internasional
Kategori	:	Jurnal	No/Vol/Tahun	:	8 / 2S7 / 2019
ISSN/ISBN	:	2277-3878
PTN/S	:	Universitas Pakuan	Program Studi	:	MATEMATIKA
Bibliography	:	1. F. D. Wihartiko, A. Buono and B. P. Silalahi. “Integer programming model for optimizing bus timetable using genetic algorithm.” IOP Conference Series: Materials Science and Engineering. Vol. 166, no. 1, pp. 1-9, 2017. 2. R. Kujala, C. Weckström R. K. Darst, M. N. Mladenović and J. Saramäki. “Data Descriptor: A collection of public transport network data sets for 25 cities.” Scientific Data, vol. .5, art. no. 180089, 2018. 3. L. Tian Z. Yunjiao and Z. Jianyou. “Application of GPS Based Inttelligent Dispatching System in Public Transportation.” Revista Ibérica de Sistemas e Tecnologias de Informação, vol. (18B), art. no. 237, 2016. 4. X. Shen S. Feng, Z. Li and B. Hu. “Analysis of bus passenger comfort perception based on passenger load factor and in‑vehicle time.” SpringerPlus, vol. 5, no. 1, art. no. 62, 2016. 5. A. Cedar, B. Golany and O. Tal. “Creating Bus Timetables with Maximal Syncronization.” Transportation Research Part A: Policy and Practice, vol. 35, no. 10, pp. 913-928, 2001. 6. V. Naumov. “Synchronisation of Timetables for Public Bus Lines Using Genetic Algorithms and Computer Simulations.” Lecture Notes in Networks and Systems, vol 36, pp. 44-53, 2018. 7. S. Chuanjiao, Z. Wei and W. Yuanqing. “Scheduling Combination and Headway Optimization of Bus Rapid Transit.” Journal of Transportation Systems Engineering and Information Technology. vol. 8, no. 5, pp. 61 – 67, 2008. 8. N. S. Bais, N. Pitale and S. Thorat. “Optimal Schedule Modeling for Public Transportasi System.” International Journal of Science and Research vol. 4, no. 4, 2015. 9. H. Mayyani, B. P Silalahi and A Aman. “Frequency Determination of Bus Rapid Transit (BRT) Applied on Service System of Trans Mataram Metro Bus to Minimize the Operational Cost.” International Journal of Engineering and Management Research. vol. 7, no. 6, pp. 134-140, 2017. 10. J. Ma, Y. Zhao, Y. Yang, T. Liu, W. Guan, J. Wang and C. “A Model for the Stop Planning and Timetables of Customized Buses.” Plos One. Vol. 12, no. 1,art. no. e0168762, 2017. 11. F. D. Wihartiko, H. Wijayanti and F. Virgantari. “Performance Comparison of Genetic Algorithms and Particle Swarm Optimization for Model Integer Programming Bus Timetabling Problem.” IOP Conference Series: Materials Science and Engineering. vol. 332, art. no. 012020, 2018.
URL	: