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An Improved Neighborhood Search of Simulated Annealing
for the Quadratic Assignment Problem (QAP)
Tan Rui Yao
Supervisor: Dr. Mohamed Saifullah Bin Hussin
Bachelor of Science (Financial Mathematics)
School of Informatics and Applied Mathematics
Quadratic Assignment Problem is one type of combinatorial optimization problems that
we face in our real life from many fields, such as social science, engineering, economic
or even on vacation planning. So far, Simulated Annealing is known as one of the most
suitable methods to solve the Quadratic Assignment Problem by obtaining a good solution
in a short period. But in fact, it still has a lot of room for improvement. In this research,
we try to propose an improvement in the neighborhood search of Simulated Annealing,
which is to use the 3-exchange neighborhood to obtain a better quality solution in a
shorter time. In the end of this research, it was expected that the outcomes would be an
improved Simulated Annealing algorithms. It will bring a great success if the
implementation of Simulated Annealing can be further optimized and improved, so that
more combinatorial problem can be solved with more effectively and efficiently in the
future.
897 | UMT UNDERGRADUATE RESEARCH DAY 2018