In cognitive radio, spectrum sensing is an important to challenge for the secondary user but not challenge for the primary user because primary give bandwidth and secondary user acquired bandwidth when two or more user acquired same bandwidth which increases the error.so reduce the false detection and increase band width is the main objective of this paper. In this paper comparison with Particl...

The marriage in honey–bees optimization (MBO) algorithm was recently proposed and showed good results for combinatorial optimization problems. Contrary to most of the swarm intelligence algorithms (such as Ant Colony Optimization), MBO uses self-organization to mix different heuristics. This paper presents a variation of the MBO algorithm where the colony contains a single queen with multiple w...

It is essential to design an appropriate submarine cable route reduce costs and improve reliability. A methodology that can be used for multi-objective optimization in planning proposed numerically studied this paper. The risks are assessed mapped the geographical map. pheromone heuristic functions of ant colony (ACO) algorithm associated with map risks, which enables it search a optimization. ...

Research in software testing has experienced a significant growth in recent years. One topic of special interest is fault detection techniques to reduce human interference and detect maximum faults. Priority is given to these techniques so that only higher priority techniques should be used instead of using individual techniques of lower priority. Bee Colony Optimization based upon natural phen...

This work presents a new multiobjective algorithm based on ant colonies, which is used in the construction of the multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes cost of the multicast tree, average delay and maximum end-to-end delay. In this way, a set of optimal solutions, know as Pareto set, is calculated in only one run of the algor...

In this paper, we present a formulation that enables Ant Colony Optimization for Continuous Domains (ACOR) to seek the optimal solution of the unit maintenance scheduling problem. ACOR is a direct extension of Ant Colony Optimization (ACO). Also it is the significant ant-based algorithm for continuous optimization. For the maintenance scheduling, cost reduction is as important as reliability. T...

Combining ant colony optimization (ACO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D), this paper proposes a multiobjective evolutionary algorithm, MOEA/D-ACO. Following other MOEA/D-like algorithms, MOEA/D-ACO decomposes an multiobjective optimization problem into a number of single objective optimization problems. Each ant (i.e. agent) is responsible for solving on...

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last decade. They are characterized by a decentralized way of working that mimics the behavior of swarms of social insects, flocks of birds, or schools of fish. The advantage of these approaches over traditional techniques is their robustness and flexibility. These properties make swarm intelligen...

This paper proposes an approximate optimization algorithm combining P systems with ant colony optimization, called ACOPS, to solve traveling salesman problems, which are well-known and extensively studied NP-complete combinatorial optimization problems. ACOPS uses the pheromone model and pheromone update rules defined by ant colony optimization algorithms, and the hierarchical membrane structur...