Improving Facility Management Performance by Optimizing Work Order Assignment with Genetic Algorithm

Higher education campus consists of diverse properties that are often divided into several zones. The FM department sets the procedures of daily work events and assigns the procedures into the workforce. The process of assigning work to FM employees, however, is non-systematic and largely depends on individuals work experience and knowledge. In this research, the authors propose the methodology to improve the work order assignment procedures by harnessing the synergism of the integration of Discrete Event Simulation (DES) and Traveling Salesman Problem (TSP) with Genetic Algorithm (GA). The algorithms help find out the best routes between many buildings that include scheduled tasks. For a verification and validation purpose, the results of the simulation are compared with actual working hours. The work order assignment optimization is performed with a case study. As a result, it was found that the optimum case reduces the total working hours relative to the baseline.