Innovative Crossover and Mutation in a Genetic Algorithm Based Approach to a Campus Bus Driver Scheduling Problem with Break Consideration and Embedded Overtime

Abstract

The unfairness of job distribution and the ineffectiveness of break-time assignment among bus drivers are factors identified as problem issues in the bus driver management in a university campus environment. The issues affect the quality of the bus service which then pointed to the efficiency or inefficiency of the bus driver sche duling system. Thus, this study investigates the problem and constraints connected to bus driver scheduling activities as a case in a ca mpus environment. Therefore, we developed an efficient bus driver scheduling model based on the Genetic Algorithm (GA) approach. The GA model is able to schedule efficiently bus drivers to working slots and break in a particular day. It is thus, a time-saving effor t and able to satisfy equal break distribution among drivers with overtime work being considered at the same time.