Kazi Irtiza Ali

Work place: Samsung Research & Development Institute Bangladesh, Sonargaon Road, Dhaka 1205, Bangladesh



Research Interests: Human-Computer Interaction


Kazi Irtiza Ali has received his B.Sc. degree in Computer Science and Engineering from Ahsanullah University of Science and Technology, Bangladesh, in 2019. He’s currently working as a User Experience Designer at Samsung Research and Development Institute Bangladesh for two years. He’s mainly involved with creating digital products for Samsung which have a huge user base. Currently his research interest is mainly focused on human-centered designs.

Author Articles
A Multi-Objective Optimization Approach for Solving AUST Classtimetable Problem Considering Hard and Soft Constraints

By Md Shahriar Mahbub Shihab Shahriar Ahmed Kazi Irtiza Ali Md. Taief Imam

DOI: https://doi.org/10.5815/ijmsc.2020.05.01, Pub. Date: 8 Oct. 2020

Preparing a class timetable or routine is a difficult task because it requires an iterative trial and error method to handle all the constraints. Moreover, it has to be beneficial both for the students and teachers. Therefore, the problem becomes a multi-objective optimization problem with a good number of constraints. There are two types of constraints: hard and soft constraint. As the problem is an NP-hard problem, population based multi-objective optimization algorithms (multi-objective evolutionary algorithm) is a good choice for solving the problem. There are well established hard constraints handling techniques for multi-objective evolutionary algorithms, however, the technique is not enough to solve the problem efficiently. In the paper, a smart initialization technique is proposed to generate fewer constraints violated solutions in the initial phase of the algorithm so that it can find feasible solutions quickly. An experimental analysis supports the assumption. Moreover, there are no well-known techniques available for handling soft constraints. A new soft constraints handing technique is proposed. Experimental results show a significant improvement can be achieved. Finally, proposed combined approach integrates smart initialization and soft constraints handling techniques. Better results are reported when comparing with a standard algorithm.

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