Modified genetic algorithm for employee work shifts scheduling optimization

Abstract

Arranging an employee shift work's schedule requires high accuracy. It is because we have to pay attention to several constraints simultaneously. The genetic algorithm presents as a method which can automatize the process of arranging the schedule as well as optimizing the result of the schedule. The Shala Bali is a hospitality business whose scheduling was complicated because of the number of the employes. This research aimed at producing a shift work schedule of the employees in a week and to know the optimum genetic algorithm parameter in this case. The constraints that were taken into account in the arrangement of the schedule included the schedule conflict of the employees in one shift, schedule conflict of employees in 1 day, the same composition of employees per shift, employees should not get morning shifts after being in night shift the night before, each shift has at least 1 employee in the front office, and each employee is required to get 1 day off within 1 schedule period. This study was able to produce an optimal work schedule of employees with crossover probability (Pc) of 0.6, and mutation probability (Pm) of 0.3. The modification algorithm in chromosome generation and chromosome structure in this study results that changes in gene length (additional number of employees) do not have to be followed by an increase in the number of chromosome populations to get optimum results.