Engineering education has a crucial role in the economic and social development of society; this paper aims to investigate the most significant factors that contributing in improving the quality of the engineering education. Furthermore, identify the factors affecting the students’ academic performance. The study was conducted by using statistical Design of Experiments (DOE) approach to investigate the main effects of lecture delivery, assessment, engagement, communication, and interaction with instructors. Minitab software is implemented to perform statistical analysis to identify the significance of each factor, and degree by which each factor influences the students’ academic achievement. Results showed that the students’ academic performance is affected by the availability of course materials, and communications with instructors.

This paper addresses a bi-criteria optimization problem to minimize total flow time and makespan simultaneously for a cellular flowshop with Sequence Dependent Setup Times (FMCSP with SDSTs); A multi-objective Particle Swarm Optimization (MPSO) and a Multi-objective Simulated Annealing (MOSA) Algorithm are proposed to solve the proposed problem. furthermore, an improved algorithm (named as IMPSO-TA), where MPSO is combined with Threshold Acceptance (TA) algorithm to improve the convergence of the obtained Pareto Fronts. The proposed algorithms are evaluated using several Quality Indicators (QI) measures for multi-objective optimization problems. Results showed that proposed algorithms can generate approximated Pareto Fronts in a reasonable CPU time. Furthermore, quality of Pareto fronts generated by IMPSO-TA is better than Pareto fronts found by MPSO and MOSA based on the test problems that are used in this research at the cost of CPU time. Further, the proposed IMPSO-TA performs as best available algorithms in the literature for small and medium test problems with a very minor deviation for best results for large test problems.