Abstract: In this study, researchers present an investigation of enhancing the capability of the Big Bang-Big Crunch (BB-BC) metaheuristic to strike a balance between diversity and quality of the search. The BB-BC is tested on three post-enrolment course timetabling problems. The BB-BC is derived from one of the evolution theories of the universe in physics and astronomy. The BB-BC theory involves two phases (big bang and big crunch). The big bang phase generates a population of random initial solutions whilst the big crunch phase shrinks those solutions to a single elite solution presented by a centre of mass. The investigation focuses on finding the significance of incorporating an elite pool and controlling the search diversity via the Euclidean distance. Both strategies provide a balanced search of diverse and good quality population. This is achieved by a dynamic changing of the population size, the utilization of elite solutions and a probabilistic selection procedure to generate a diverse collection of promising elite solutions. The investigation is conducted in three stages, first researchers apply the original BB-BC with an iterated local search; second researchers apply the BB-BC with an elite pool and an iterated local search without considering the Euclidean distance and third researchers apply the BB-BC with an elite pool and a simple descent heuristic with utilizing the Euclidean distance. It is found that by incorporating an elite pool without using the Euclidean distance, the BB-BC performs better than the original BB-BC. However, utilizing both elite pool and Euclidean distance have a greater impact on the BB-BC. The third version of BB-BC performs better than both previous versions. Experiments showed that the third version produces high quality solutions and outperforms some approaches reported in the literature.