The existing ant colony optimization (ACO) algorithms for the quadratic assignment problem
(QAP) are often combined with two kinds of stochastic local search (SLS) methods: the 2-opt …

The quadratic assignment problem (QAP) is a well known important combinatorial problem.
Indeed, many real world applications such as backboard wiring, typewriter keyboard design …

In recent years, various metaheuristic approaches have been created to solve Quadratic
Assignment Problems (QAPs). Among others is the Ant Colony Optimization (ACO) …

Quadratic assignment problem (QAP) is one of the most difficult combinatorial optimization
problems which has been tackled by many metaheuristic algorithms. This paper proposes a …

A simulated annealing ant colony algorithm (ASAC) is presented to tackle the quadratic
assignment problem (QAP). The simulated annealing method is introduced to the ant colony …

Ant colony optimization algorithms are currently among the best performing algorithms for
the quadratic assignment problem. These algorithms contain two main search procedures …

Abstract Ant Colony Optimization (ACO) algorithms construct solutions each time starting
from scratch, that is, from an empty solution. Similar to ACO, Iterated Greedy is a constructive …

The previously proposed cunning ant system (c AS), a variant of the ACO algorithm, worked
well on the TSP and the results showed that the c AS could be one of the most promising …

Recently symmetric multi processing (SMP) has become available at a reasonable cost. In
this paper, we propose several types of parallel ACO algorithms with SMP for solving the …

Ant colony optimization (ACO) algorithms construct solutions each time starting from scratch,
that is, from an empty solution. Differently from ACO algorithms, iterated greedy, another …