The production of commercial DNA microarrays is based on a light-directed chemical synthesis driven by a set of masks or micromirror arrays. Because of the natural properties of light and the ever shrinking feature sizes, the arrangement of the probes on the chip and the order in which their nucleotides are synthesized play an important role on the quality of the final product. We propose a new...

In this work we present a simple, but effective method of enhancing and exploiting diversity from multiple packet transmissions in systems that employ nonbinary linear modulations such as PSK and QAM. This diversity improvement results from redesigning the symbol mapping for each packet transmission. Using a general framework for evaluating the upper bound of bit error rate (BER) with multiple ...

This paper presents an improved as well as a completely new version of a mixed integer linear programming (MILP) formulation for solving the quadratic assignment problem (QAP) to global optimum. Both formulations work especially well on instances where at least one of the matrices is sparse. Modification schemes, to decrease the number of unique elements per row in symmetric instances, are pres...

In this work, we introduce the variance expression for quadratic assignment problem (QAP) costs. We also de;ne classes of QAP instances, described by a common linear relaxation form. The use of the variance in these classes leads to the study of isomorphism and allows for a de;nition of a new di"culty index for QAP instances. This index is then compared to a classical measure found in the liter...

This paper compares some of the most efficient heuristic methods for the quadratic assignment problem. These methods are known as strict taboo search, robust taboo search, reactive taboo search and genetic hybrids. It is shown that the efficiency of these methods strongly depends on the problem type and that no one method is better than all the others. A fast method for tuning the short term me...

An instance of the quadratic assignment problem (QAP) with cost matrix Q is said to be linearizable if there exists an instance of the linear assignment problem (LAP) with cost matrix C such that for each assignment, the QAP and LAP objective function values are identical. The QAP linearization problem can be solved in O(n) time. However, for the special cases of Koopmans-Beckmann QAP and the m...

Program libraries are one tool to make the cooperation between specialists from various elds successful: the separation of application-speci c knowledge from applicationindependent tasks ensures portability, maintenance, extensibility, and exibility. The current paper demonstrates the success in combining problem-speci c knowledge for the quadratic assignment problem (QAP) with the raw computin...

The quadratic assignment problem (QAP) belongs to the class of NP -hard combinatorial optimization problems. Although it has been studied extensively over the past 35 years, problems of size n 15 still prove to be intractable. Since good lower bounds are necessary to solve larger problem instances, we discuss the class of eigenvalue bounds for QAP and extend previous results of these continuous...

We investigate a special case of the maximum quadratic assignment problem where one matrix is a product matrix and the other matrix is the distance matrix of a one-dimensional point set. We show that this special case, which we call the Wiener maximum quadratic assignment problem, is NP-hard in the ordinary sense and solvable in pseudo-polynomial time. Our approach also yields a polynomial time...

Variances of solution values that can be calculated in polynomial time may be associated with an instance of the Quadratic Assignment Problem (QAP). The problem of graph isomorphism can be modeled as a QAP, associating each data matrix with each graph. In this work, we look for invariant edge weight functions for the graphs composing the instances in order to try to find quantitative difference...