01741nas a2200217   4500000000100000000000100001008004100002260001200043653003100055653002600086653002400112653003300136100001800169700002600187245006600213856009500279300001000374490000600384520111900390022001401509       2019                            d  c03/201910aCombinatorial Optimization10aGolden Ball Algorithm10aSimulated Annealing10aQuadratic Assignment Problem1 aFatima Sayoti1 aMohammed Essaid Riffi00aHybrid Algorithm for Solving the Quadratic Assignment Problem  uhttp://www.ijimai.org/journal/sites/default/files/files/2017/10/ijimai_5_4_8_pdf_86744.pdf  a68-740 v53 aThe Quadratic Assignment Problem (QAP) is a combinatorial optimization problem; it belongs to the class of NP-hard problems. This problem is applied in various fields such as hospital layout, scheduling parallel production lines and analyzing chemical reactions for organic compounds. In this paper we propose an application of Golden Ball algorithm mixed with Simulated Annealing (GBSA) to solve QAP. This algorithm is based on different concepts of football. The simulated annealing search can be blocked in a local optimum due to the unacceptable movements; our proposed strategy guides the simulated annealing search to escape from the local optima and to explore in an efficient way the search space. To validate the proposed approach, numerous simulations were conducted on 64 instances of QAPLIB to compare GBSA with existing algorithms in the literature of QAP. The obtained numerical results show that the GBSA produces optimal solutions in reasonable time; it has the better computational time. This work demonstrates that our proposed adaptation is effective in solving the quadratic assignment problem.  a1989-1660