A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation...

Swarm intelligence is a relatively novel approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful one is the ant colony optimization. Ant colony optimization (ACO) algorithm, a novel population-based and meta-heuristic app...

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...

Ant Colony Optimization (ACO) [2] is a nondeterministic algorithm framework that mimics the foraging behavior of ants to solve difficult optimization problems. Several researchers have successfully applied ant based algorithm framework in different fields of engineering, but never in VLSI testing. In this paper, we first describe the basics of ACO. We then consider the problem of simultaneously...

ACO-based transmission scheme, named the Unity of MPEE and MPEB (UMM), is proposed to improve the longevity of WSNs. Different from general transmission methods, it has two distinct characteristics: First, by considering energy consumption in different areas, it achieves not only Maximum Possible Energy Efficiency MPEE and also Maximum Possible Energy Balancing MPEB, and finally prolongs the ne...

Time constraint is the main factor in real time operating system. Different scheduling algorithm is used to schedule the task. The Earliest Deadline First and Ant Colony Optimization is a dynamic scheduling algorithm used in a real time system and it is most beneficial scheduling algorithm for single processor real-time operating systems when the systems are preemptive and under loaded. The mai...

Travelling Salesman Problem (TSP) is a classical combinatorial optimization problem. This problem is NP-hard in nature. Meta-heuristic approaches have proved to be quite useful for approximate solution of difficult combinatorial optimization problems. Ant colony optimization is one of the popular Meta-heuristics and is unique on the basis of its distributed computation and indirect communicatio...

Ant Colony Optimization (ACO) is recently proposed metaheuristic approach for solving hard combinatorial optimization problems. Parallel implementation of ACO can reduce the computational time obviously. An improved parallel ACO algorithm is proposed in this paper, which use dynamic transition probability to enlarge the search space by stimulating ants choosing new path at early stage; use poly...

In this paper we describe the design of a fuzzy logic controller for the ball and beam system using a modified Ant Colony Optimization (ACO) method for optimizing the type of membership functions, the parameters of the membership functions and the fuzzy rules. This is achieved by applying a systematic and hierarchical optimization approach modifying the conventional ACO algorithm using an ant s...