Using harmony search for optimising university shuttle bus driver scheduling for better operational management

Managing human resource to achieve specific goal in an organisation is a crucial task. One of various aspects in managing human resource is preparing optimum scheduling to perform certain tasks. The main objective of this paper is to illustrate the preparation and the work of optimum scheduling for university shuttle bus driver using a recently develop meta-heuristic technique known as Harmony Search. A mathematical formulation for the university shuttle bus driver scheduling problem based on the requirement and the preference of the university is illustrated. The optimum schedule is generated using Harmony Search, an optimisation approach inspired by the processes in music improvisation with less mathematical computation. It can be seen that the result produced using harmony search approach to automate the optimum university shuttle bus driver scheduling is quite promising because it yield better value of objective function compared with the one being done manually. Automation of the optimum university bus driver scheduling certainly can enhanced the operational management processes. This work can be regarded as a multidisciplinary work which several domains such as computer science, mathematics, operational research and management are involved

Optimization in driver’s scheduling for university shuttle bus using harmony search

This paper is about driver scheduling which is categorized as a difficult combinatorial problem. Driver scheduling is the process of assigning shift to the drivers based on hard and soft constraints. The proposed technique is Harmony Search, which is a recently developed population-based meta heuristic optimization algorithm. This study will be implemented to UTeM Shuttle Bus. The number of drivers involved is about 25. It is viewed that the objective function evaluated by Harmony Search is less than a manual solution. Therefore, the result produced for this project is quite promising since the objective function obtained is better than the real schedule which is done manually