| dc.description.abstract | This thesis focused on the primary problem of optimizing the scheduling for maintenance of
combined harvester to minimize the total cost and reduce the interruption during the process of
harvesting rice. To increase the ability of conducting many repairs within one system of
combined harvester or postpone the task into the next day, the mathematical model is used to
modify the system and propose the optimized maintenance schedule for workforce problems.
This MILP model concept is first applied to CPLEX software to give the optimal solution. Then,
it was reimplemented using metaheuristics technique, specifically Particle Swarm Optimization
Algorithm to effectively tackle the larger data of the problem by Python code. After having the
result, the sensitivity analysis is applied to evaluate the efficiency of this methodologies. | en_US |
