The article introduces QAPLIB, a comprehensive library of data instances for the Quadratic Assignment Problem (QAP), a significant challenge in combinatorial optimization. The library, first published in 1991, has been updated to include new problem instances and the best known feasible solutions and lower bounds. The current version is available on the World Wide Web at two URLs: http://www.opt.math.tu-graz.ac.at/~karisch/qaplib and http://www.diku.dk/~karisch/qaplib. The library includes instances of various sizes, with the largest being of size \( n = 256 \). Each instance is characterized by its generation method and is pure quadratic, with symmetric properties unless otherwise stated. The problem data is formatted as follows: \( \begin{array}{ll} n & \\ A & \\ B \end{array} \), where \( n \) is the instance size, and \( A \) and \( B \) are either flow or distance matrices. The QAPLIB also includes a list of recent dissertations related to QAP, reflecting the increased research activities in this area.The article introduces QAPLIB, a comprehensive library of data instances for the Quadratic Assignment Problem (QAP), a significant challenge in combinatorial optimization. The library, first published in 1991, has been updated to include new problem instances and the best known feasible solutions and lower bounds. The current version is available on the World Wide Web at two URLs: http://www.opt.math.tu-graz.ac.at/~karisch/qaplib and http://www.diku.dk/~karisch/qaplib. The library includes instances of various sizes, with the largest being of size \( n = 256 \). Each instance is characterized by its generation method and is pure quadratic, with symmetric properties unless otherwise stated. The problem data is formatted as follows: \( \begin{array}{ll} n & \\ A & \\ B \end{array} \), where \( n \) is the instance size, and \( A \) and \( B \) are either flow or distance matrices. The QAPLIB also includes a list of recent dissertations related to QAP, reflecting the increased research activities in this area.