Swarm intelligence has been successfully applied in various domains, e.g., path planning, resource allocation and data mining. Despite its wide use, a theoretical framework in which the behavior of swarm intelligence can be formally understood is still lacking. This article starts by formally deriving the evolutionary dynamics of ant colony optimization, an important swarm intelligence algorith...

in this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. two objective functions, real power loss and energy not supplied index (ens), were utilized. multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optim...

The fixed-charge Capacitated Multi-commodity Network Design (CMND) is a well-known problem of both practical and theoretical significance. Network design models represent a wide variety of planning and operation management issues in transportation telecommunication, logistics, production and distribution. In this paper, Ant Colony Optimization (ACO) based neighborhoods are proposed for CMND pro...

The maintenance scheduling of thermal generators is a large-scale combinatorial optimization problem with constraints. In this paper we introduce the Rank-Based Ant System algorithm based version of the Ant System. This algorithm reinforces local search in neighborhood of the best solution found in each iteration while implementing methods to slow convergence and facilitate exploration.Rank-Bas...

In this paper we present two versions of AntNet, a novel approach to adaptive learning of routing tables in wide area best-effort datagram networks. AntNet is a distributed multi-agent system inspired by the stigmergy model of communication observed in ant colonies. We report simulation results for AntNet on realistically sized networks using as performance measures throughput, packet delays an...

The basic ant colony algorithm for mobile robot path planning has many problems, such as lack of stability,algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes four improvement measures. 1. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm; 2. Apply max min ant method to ...

The basic ant colony algorithm in the welding robot path planning, in the search process, prone to search for too long, low efficiency, easy to fall into the local optimal and other issues. In this paper, the basic ant colony algorithm is improved, and the Adadelta algorithm is introduced. By combining the basic ant colony algorithm and Adadelta algorithm, the probability of selecting the next ...

This paper introduces AntNet, a novel adaptive approach to routing tables learning in connectionless communications networks. AntNet is inspired by the stigmergy communication model observed in ant colonies. We compare AntNet with the current Internet routing algorithm (OSPF), some old Internet routing algorithms (SPF and distributed adaptive Bellman-Ford), and recently proposed forms of asynch...