ANA: Ant Nesting Algorithm for Optimizing Real-World Problems

Ant-Stigmergy Algorithm on Real-World Continuous Optimization Problems

Ants have always fascinated human beings. What particularly strikes the occasional observer as well as the scientist is the high degree of societal organization that these insects can achieve in spite of very limited individual capabilities (Dorigo et al., 2000). Ants have inspired also a number of optimization algorithms. These algorithms are increasingly successful among researches in compute...

Applications of the Differential Ant-Stigmergy Algorithm on Real-World Continuous Optimization Problems

Optimizing Dijkstra for real-world performance

Using Dijkstra’s algorithm to compute the shortest paths in a graph from a single source node to all other nodes is common practice in industry and academia. Although the original description of the algorithm advises using a Fibonacci Heap as its internal queue, it has been noted that in practice, a binary (or d-ary) heap implementation is significantly faster. This paper introduces an even fas...

Optimizing Outbreak Detection for Real World Networks

Influence Maximization and outbreak detection are two problems that have seen massive research in recent years, for good reason. For example, targeted tweets by well-selected Twitter users can lead to massive reshares, resulting in a quick dissemination of information. Well-placed sensors can allow contamination in a water pipeline network to be detected quickly. Although the two problems may s...

Cultural Ant Algorithm for Continuous Optimization Problems

In order to overcome prematurity of ant colony algorithm, the conception of belief space originated in cultural algorithm is introduced, and a new cultural ant algorithm is proposed for continuous optimization problems. Firstly, the coding scheme for ant colony algorithm to solve continuous optimization problems is discussed. Then belief space is brought in, and designed as the form of two part...