Each university has different regulations in making lecture schedule according to the conditions of respective
institution. In this study, regulation on lecture scheduling used the maximum limit of credits of lecturer in a day, in which
if exceeds the maximum limit, then the schedule of course will be moved on another day. This study attempts to optimize
the schedule preparation in each semester by considering the maximum limit of credits of a lecturer in a day. Lecture
scheduling is a combination of space, time, and resources. It is categorized into combinatorial optimization group. There
are two methods for solving the combinatorial optimization problems, i.e. exact and approximation method. The
approximation method consists of two types, heuristics and metaheuristics. The algorithm metaheuristics categories include
genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), bee colony optimization
(BCO), simulated annealing, and so on. This paper employed metaheuristics approach. Research on the preparation of
lecture scheduling using ACO algorithm has been conducted and proven to be able to prepare the lecture scheduling. The
ACO algorithm has numbers of parameters that in solving issues, one must manually set a number of parameters by using
the Design of Experiments (DoE) tool, which takes time to solve the optimization problem. Hence, to solve the issue, an
automated parameter optimization is required. PSO algorithm has fewer parameters compared to the ACO. Therefore, the
purpose of this paper is a hybrid between PSO and ACO in preparing lecture scheduling