Ant Colony Optimisation (ACO) algorithms are inspired by the foraging behaviour of real ants and are a relatively new class of algorithm which have shown promise when applied to combinatorial optimisation problems. In recent years ACO algorithms have begun to gain popularity and as such are beginning to be applied to more complex problem domains including (but not limited to) dynamic problems. ...

We propose an algorithm based on the Ant Colony Optimization (ACO) meta-heuristic for solving the Multidimensional Knapsack Problem (MKP), the goal of which is to find a subset of objects that maximizes a given objective function while satisfying some resource constraints. The proposed ACO algorithm is generic, and we propose three different instantiations, corresponding to three different ways...

The Ant Colony Optimization algorithms (ACO) are computational models inspired by the collective foraging behavior of ants. By looking at the strengths of ACO, they are the most appropriate for scheduling of tasks in soft real-time systems. In this paper, ACO based scheduling algorithm for real-time operating systems (RTOS) has been proposed. During simulation, results are obtained with periodi...

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 ...

In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multi-objective ACO optimizer approach problems many objective functions. This proposal is suitable if the preferences of Decision Maker (DM) can be modeled through relations. The introduced algorithm (Interval Outranking-based ACO, IO-ACO) first ant-colony that embeds an model bear vagueness an...

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integra...