Modified sine cosine algorithm for solving quadratic assignment problem.

Quadratic Assignment Problem (QAP) is one of the famous combinatorial optimization problems in operational research field. In this problem, a set of facilities is assigned to a set of locations in form of one-to-one assignment with the goal to obtain minimum assignment cost. Since QAP is classified under NP-hard problem, a metaheuristics approach is more appropriate for finding a good solution especially when the problem size increased. Sine Cosine Algorithm (SCA) can be categorized under population-based method which shown such an excellent performance in solving various optimization problem. SCA came up with high quality solutions and performed well due to its ability in stabilizing between exploration and exploitation phases evenly during the search process for optimal solution. However, this approach is rarely used to solve discrete optimization problem such as QAP. This is because the nature of its solution search which produce continuous values for new solution based on the concept of sine cosine principle makes it challenging in solving discrete optimization problem. Hence, this study aims to modify the SCA on its acceptance criteria based on the concept of sine cosine to solve discrete optimization problem, to solve QAP and evaluate its solution performance. The instances from QAPLIB were tested. The computational results shows that the modified SCA is an effective and superior method in solving QAP when compared to the best-known solutions presented in previous studies. [ABSTRACT FROM AUTHOR]