In this paper, we show that the quadratic assignment problem (QAP) can be reformulated to an equivalent rank constrained doubly nonnegative (DNN) problem. Under framework of difference convex functions (DC) approach, a semi-proximal DC algorithm is proposed for solving relaxation DNN whose subproblems solved by augmented Lagrangian method. We generated sequence converges stationary point corres...

The Antlion Optimization (ALO) algorithm is a meta-heuristic optimization based on the hunting of ants by antlions. basic inadequacy this that it has long run time because random walk model used for ant's movement. We improved some mechanisms in ALO algorithm, such as ants' walking, reproduction, sliding towards antlion, elitism, and selection procedure. This proposed called Improved (IALO) alg...

routines for approximate solution of dense quadratic assignment problems A greedy randomized adaptive search procedure for the quadratic assignment problem, in Quadratic assign-for approximate solution of sparse quadratic assignment problems using

Several real-life applications can be stated in terms of the Quadratic Assignment Problem. Finding an optimal assignment is computationally very difficult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver impr...

The Quadratic Assignment Problem (QAP) is an NP-complete problem. Different algorithms have been proposed using different methods. In this paper, the problem is formulated as a minimizing problem of a quadratic function with restrictions incorporated to the computational dynamics and variables Si {1,2,..., n}. To solve this problem a recurrent neural network multivalued (RNNM) is proposed. We ...

The quadratic assignment problem (denoted QAP), in the trace formulation over the permutation matrices, is min X2 tr(AXB + C)X t : Several recent lower bounds for QAP are discussed. These bounds are obtained by applying continuous optimization techniques to approximations of this combinatorial optimization problem, as well as by exploiting the special matrix structure of the problem. In particu...