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 ...

For the cloud database route scheduling problem, this paper designed a cloud database route scheduling algorithm according to the dynamic combination of the genetic algorithm and ant colony algorithm. The initial solution got by the Genetic Algorithm was transformed into the pheromone initial value, which was needed by ant colony algorithm, then the optimal solution by the ant colony algorithm ...

The crowding population based ant colony optimization algorithm (CP-ACO) uses a different pheromone update in comparison to other ACO algorithms. In this paper, crowding population based ant colony optimization algorithm is proposed to solve service restoration problem. The most notable achievement featured in this paper is run time reduction of algorithm to solve the service restoration task. ...

In this paper, 2D seismic data and petrophysical logs of the Pabdeh Formation from four wells of the Mansuri oil field are utilized. ΔLog R method was used to generate a continuous TOC log from petrophysical data. The calculated TOC values by ΔLog R method, used for a multi-attribute seismic analysis. In this study, seismic inversion was performed based on neural networks algorithm and the resu...

To solve the problem of vehicle routing problem under capacity limitation, this paper puts forward a novel method of logistics distribution route optimization based on genetic algorithm and ant colony optimization algorithm (GA-ACO). On the first stage, improved genetic algorithm with a good global optimization searching ability is used to find the feasible routes quickly. On the second stage, ...

Nowadays, path planning has become an important field of research focus. Considering that the ant colony algorithm has numerous advantages such as the distributed computing and the characteristics of heuristic search, how to combine the algorithm with two-dimension path planning effectively is much important. In this paper, an improved ant colony algorithm is used in resolving this path plannin...

The conventional classification task of data mining can be called single-label classification, since there is a single class attribute to be predicted. This paper addresses a more challenging version of the classification task, where there are two or more class attributes to be predicted. We propose a new ant colony algorithm for the multi-label classification task. The new algorithm, called Mu...

In optimization problem, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have been known as good alternative techniques. GA is designed by adopting the natural evolution process, while ACO is inspired by the foraging behaviour of ant species. This paper presents a hybrid GA-ACO for Travelling Salesman Problem (TSP), called Genetic Ant Colony Optimization (GACO). In this metho...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

I Which size? Trade-off I Minimum size: connectivity by recombination is achieved if at least one instance of every allele is guaranteed to be be present at each locus. Ex: if binary: P∗ 2 = (1− (0.5) ) for l = 50, it is sufficient M = 17 to guarantee P∗ 2 > 99.9%. I Often: independent, uninformed random picking from given search space. I Attempt to cover at best the search space, eg, Latin hyp...