Orthogonal frequency division multiplexing (OFDM) has been considered for visible light communication (VLC) thanks to its ability to boost data rates as well as its robustness against frequency-selective fading channels. A major disadvantage of OFDM is the large dynamic range of its time-domain waveforms, making OFDM vulnerable to nonlinearity of light emitting diodes (LEDs). DC biased optical ...

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

  In this paper an Ant Colony (ACO) algorithm is developed to solve aircraft recovery while considering disrupted passengers as part of objective function cost. By defining the recovery scope, the solution always guarantees a return to the original aircraft schedule as soon as possible which means least changes to the initial schedule and ensures that all downline affects of the disruption are ...

Ant colony optimization(ACO), which is one of the intelligential optimization algorithm, has been widely used to solve combinational optimization problems. Deceptive problems have been considered difficult for ant colony optimization. It was believed that ACO will fail to converge to global optima of deceptive problems. This paper proves that the first order deceptive problem of ant colony algo...

In this paper, we present a novel approach named "ACO-PSO-TSPGPU" to run PSO and ACO on Graphical Processing Units (GPUs) and applied to TSP (Parallel-PSO&ACO-A-TSP). Both algorithms are implemented on GPUs. Well-known benchmark problems for many heuristic and meta heuristic algorithms presented by Travelling Salesman Problem (TSP) are known as NP hard complex problems.TSP was investigated usin...

An Adaptive Cubic Overestimation (ACO) framework for unconstrained optimization was proposed and analysed in Cartis, Gould & Toint (Part I, 2007). In this companion paper, we further the analysis by providing worst-case global iteration complexity bounds for ACO and a second-order variant to achieve approximate first-order, and for the latter even second-order, criticality of the iterates. In p...

Swarm Intelligence (SI) is a relatively new technology that takes its inspiration from the behavior of social insects and flocking animals. In this paper, we focus on two main SI algorithms: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). An extension of ACO algorithm and a PSO algorithm has been implemented to solve the portfolio optimization problem, which is a continuous...

Ant Colony Optimisation (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. ACO implementations are typically tailored in an ad hoc manner to suit particular problems. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some r...

In this paper, we implement Ant Colony Optimization (ACO) for sequence alignment. ACO is a meta-heuristic recently developed for nearest neighbor approximations in large, NP-hard search spaces. Here we use a genetic algorithm approach to evolve the best parameters for an ACO designed to align two sequences. We then used the best parameters found to interpolate approximate optimal parameters for...

Strong Negative Difference Effect (NDE) is present on Mg alloys in [mPEG n MPyr]ClO 4 -H 2 O and [BMPyr]AcO-H but not MPyr]AcO-H mixtures. The role of MPyr] + its synergy with AcO - water-ionic liquids mixtures were characterized combining surface analysis by ToF-SIMS, solution vibration spectroscopies molecular dynamics simulations. NDE was explained the “free” water phase formation when 2+ -i...