Abstract

This research paper examines the usage of combining the meta-heuristic approaches for solving critical real-world optimization problems due to the hard and soft constraints. For the last few decades, developing an optimal solution for these problems were considered as a difficult task, and manual timetabling required an excessive amount of effort and time to deliver the quality results. This paper's objective is to address several approaches and develop a generic solution for solving a wide range of timetabling and scheduling problems. Many techniques and benchmark instances have been reviewed and presented to find a feasible solution in the literature section. This paper also investigates the performance based on the combination of meta-heuristic approaches to solve the problem and introduce the algorithm to allocate time slots to several resources according to their constraints satisfaction and violations. However, this algorithm may consider as a comprehensive benchmark instance and significant improvement for future researchers. Furthermore, the computational and experimental results of the algorithm determine the feasibility, effectiveness, robustness, and optimality of the proposed approach.

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