A fuzzy cloud resource scheduling model with time-cost constraints is built using triangular numbers to represent uncertain task execution time. Task reduces total time and cost spent on a project. It connects virtual machines functions. Particle swarm optimization (HPO) used plan resources (HSOA). The approach uses orthogonal particle initialization increase the quality of initial exploration,...

Particle swarm optimization (PSO) is a Swarm Intelligence technique used for optimization motivated by the social behavior of individuals in large groups in nature. The damped mass-spring analogy known as the PSO continuous model allowed us to derive a whole family of particle swarm optimizers with different properties with regard to their exploitation/exploration balance. Using the theory of s...

Clustering is the process of organizing similar objects into groups, with its main objective of organizing a collection of data items into some meaningful groups. The problem of Clustering has been approached from different disciplines during the last few year's. Many algorithms have been developed in recent years for solving problems of numerical and combinatorial optimization problems. M...

In this paper, we study discrete swarm algorithms, where mobile robots (or “mobots”) move around interacting in an environment to solve computational problems. This work extends recent work on swarm algorithms in the distributed computing, artificial intelligence, and robotics literatures in that we assume that mobots are computational, that is, they have additional memory and hardware so as to...

In this paper, cantilever retaining wall design is studied as an important optimization task in civil engineering. The current study explores the efficiency of some recent swarm intelligence techniques: accelerated particle swarm optimization (APSO), firefly algorithm (FA), and cuckoo search (CS). These algorithms are verified using two benchmark case studies. In order to better determine the p...

Particle swarm optimization (PSO) algorithm is a kind of random optimization algorithm based on swarm intelligence. Swarm intelligence of PSO is produced by cooperation and competition between particles, which is used for guiding optimization search. PSO has been studied widely in many applications due to its good global searching ability. Currently PSO has been widely used in function optimiza...

Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, it focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. The characterizing property of a swarm intelligence system i...

This paper presents a novel approach to approve better network lifetime with the help of Swarm Intelligence (SI) technique which serves an ideal model of formulating routing protocols for WSNs. In this paper, wireless sensor network is firstly deployed and secondly the sensor nodes are communicated among themselves with the help of Ant Colony Optimization (ACO) so that it can find out the short...

The social insect metaphor for solving problems has become an emerging topic in the recent years. This approach emphasizes on direct or indirect interactions among simple agents. Swarm Intelligence is the collective behavior of decentralized [8], self-organized [4] system whereby the collective behavior of agent interacting locally with the environment causes coherent global pattern to emerge. ...