Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem...

Mobile Ad hoc network consists of a set of mobile nodes. It is a dynamic network which does not have fixed topology. This network does not have any infrastructure or central administration, hence it is called infrastructure-less network. The change in topology makes the route from source to destination as dynamic fixed and changes with respect to time. The nature of network requires the algorit...

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foragi...

We show the emergence of Swarm Intelligence in physical robots. We transfer an optimization algorithm which is based on beeforaging behavior to a robotic swarm. In simulation this algorithm has already been shown to be more effective, scalable and adaptive than algorithms inspired by ant foraging. In addition to this advantage, bee-inspired foraging does not require (de-)centralized simulation ...

A recently proposed swarm intelligence technique for Fuzzy Cognitive Map learning is described. The technique employs the Particle Swarm Optimization algorithm to minimize a proper objective function, whose global minimizers correspond to suboptimal weight matrices of the Fuzzy Cognitive Map. New instances of an industrial test problem are studied, justifying the usefulness of the technique as ...

Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable ...

Currently, swarm robotics is one of the most promising technologies in computer science. As technologies become smarter, the potential for swarm robotics improve and the coordination of multi robot system finds applications in various fields. This paper adds new perspective to autonomous cars by proposing to incorporate swarm robotics into it. This paper summarizes various algorithms used in sw...

This paper assumes each user has more than one queue, derives a new packet dependent proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new schemes of cross-layer packet dependent OFDM scheduling for heterogeneous classes of traffic based on proportional fairness. Scenario 1, scenario 2 and scenario 3 lea...

The catfish particle swarm optimization (CatfishPSO) algorithm is a novel swarm intelligence optimization technique. This algorithm was inspired by the interactive behavior of sardines and catfish. The observed catfish effect is applied to improve the performance of particle swarm optimization (PSO). In this paper, we propose fuzzy CatfishPSO (F-CatfishPSO), which uses fuzzy to dynamically chan...