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...

The effect of plant growth-promoting bacteria inoculation on plant growth and the sugar content in Agave americana was assessed. The bacterial strains ACO-34A, ACO-40, and ACO-140, isolated from the A. americana rhizosphere, were selected for this study to evaluate their phenotypic and genotypic characteristics. The three bacterial strains were evaluated via plant inoculation assays, and Azospi...

Groundwater long-term monitoring (LTM) is required to assess human health and environmental risk of residual contaminants after active groundwater remediation activities are completed. However, LTM can be costly because of the large number of sampling locations that exist at a site from previous site characterization and remediation activities. The cost of LTM may be reduced by identifying redu...