Genetic Algorithm Based Heuristic for Constrained Industry Factory Workforce Scheduling

Scheduling is a task of dividing the resources such as human, assets according to the constraint satisfaction, time, and priority. Workforce scheduling is one of the typical problems which involved many constraints and requirement that appear in many workplaces. It is a very tough and time-consuming task when many requirements and constraints need to be considered. In this research project, the genetic algorithm approach is studied and applied to find a cyclic schedule that will satisfy all the specific constraints. A two-dimensional array is used as the chromosome representation of the schedule. The fitness function in this problem is a function to calculate the total penalty of the schedule generated. Genetic algorithms are used in this research to generate an automated solution for the workforce schedule that satisfied all the legal requirements and constraints. The algorithm is tested and verified using the benchmark dataset.