The classic Quadratic Assignment Problem (QAP) is one of the most interesting and challenging combinatorial optimization problems in existence. Since QAP is NP-complete, it is notoriously difficult to be solved by exact solution methods. This paper focuses on the intelligent solution methods, particularly, genetic algorithms, and related development on QAP. A hybrid genetic algorithm is devised...

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first o...

a new powerful optimization algorithm inspired from colonizing weeds is utilized to solve the well-known quadratic assignment problem (qap) which is of application in a large number of practical areas such as plant layout, machinery layout and so on. a set of reference numerical problems from qaplib is taken in order to evaluate the efficiency of the algorithm compared with the previous ones wh...

The Quadratic Assignment Problem (QAP) is one of the most interesting and most challenging combinatorial optimization problems in existence. This thesis will be a survey of the QAP. An introduction discussing the origins of the problem will be provided first. Next, formal problem descriptions and mathematical formulations will be given. Issues pertaining to the computational complexity of the Q...

We model the problem of monolingual textual alignment as a Quadratic Assignment Problem (QAP) which simultaneously maximizes the global lexicosemantic and syntactic similarities of two sentence-level texts. Because QAP is an NP-complete problem, we propose a branch-and-bound approach to efficiently find an optimal solution. When compared with other methods and studies, our results are competitive.

The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearization are tight, but hardly exploited within a reasonable computing time because of their size. On the other hand, Kaufman and Broeckx formulation [1] is the smallest of these linearizations, but very wea...

It is often difficult to verify the solutions of computationally intensive mathematical optimization problems. Metamorphic testing is a technique to verify software test output even when a complete testing oracle is not present. We apply metamorphic testing to a classic optimization problem, the quadratic assignment problem (QAP). A number of metamorphic relations for the QAP are described in d...

Quadratic assignment problem (QAP) is one of fundamental combinatorial optimization problems in many fields. Many real world applications such as backboard wiring, typewriter keyboard design and scheduling can be formulated as QAPs. Ant colony algorithm is a multi-agent system inspired by behaviors of real ant colonies to solve optimization problems. Ant colony optimization (ACO) is one of new ...

The paper proposes, compares and analyses different memory-based meta-heuristics for the quadratic assignment problem (QAP). Two of these methods (FANT and GDH) are new while two others (HAS-QAP and GTSH) are among the best for structured QAP instances. These methods are based on ant systems and genetic algorithms and they are presented under a unified general scheme, called adaptive memory pro...