Optimization of Private Bus Scheduling in UiTM Shah Alam Using Integer Linear Programming

Authors

  • Norlenda Mohd. Noor Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Malaysia
  • Zuraida Alwadood Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Malaysia
  • Nuramelissa Ahmad Murad Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Malaysia
  • Nur Maisarah Mohamad Termizi Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Malaysia

Keywords:

Bus scheduling, optimization, integer linear programming

Abstract

Bus usage among students are common in any higher learning institutions, simply because it is the cheapest transportation mode that the student could afford. In UiTM Shah Alam, there are 2 types of bus provider: one that is provided by UiTM itself and two, by a private company, appointed by UiTM. In this paper, scheduling of private bus services is presented. The problems arise in this area involved long waiting time and the unavailability of bus schedule that students can rely on. The objective of this project is on planning a schedule of the private bus service that will optimize the number of trips taken by each bus according to passenger, based on peak/off-peak hours. However, this study will only focus on zone Section 7 and Dalaman since these two zones are the mostly used by students. A reference model in scheduling of UiTM bus using integer linear programming has been applied and enhanced in this project. The variables are arranged according to the constraints in Microsoft Excel and later MATLAB Software is used to generate the results. Using optimization toolbox, the bus schedule for route Section 7 and Dalaman are generated, which optimized the number of trips taken by each bus. The schedule is arranged according to the peak hours and off-peak hours of bus service time. Result shows that the objective is achieved. However, a system that combines both private and UiTM bus is recommended to be developed in the future, as it is believed that resources such as time and money can further optimize the scheduling problem.

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Published

2023-10-18
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