The diversity and applicability of swarm intelligence is increasing everyday in the fields of science and engineering. Swarm intelligence gives the features of the dynamic features optimization concept. We have used swarm intelligence for the process of feature optimization and feature selection for content-based image retrieval. The performance of content-based image retrieval faced the proble...

Swarm Intelligence algorithms have proved to be very effective in solving problems on many aspects of Artificial Intelligence. This paper constitutes a first study of the recently proposed Unified Particle Swarm Optimization algorithm on scheduling problems. More specifically, the Single Machine Total Weighted Tardiness problem is considered, and tackled through a scheme that combines Unified P...

Partner selection is a critical issue in the research of virtual enterprise. It is usually a combinatorial optimization problem. In this paper, an improved discrete particle swarm algorithm is proposed for the partner selection optimization. At first, an optimization model is presented, which includes the main crucial factors for partner selection, such as running cost, reaction time and failur...

This chapter introduces the methodology of particle swarm optimization algorithm usage as a tool for finding customer profiles based on a previously developed predictive model that predicts events like selection of some products or services with some probabilities. Particle swarm optimization algorithm is used as a tool that finds optimal values of input variables within developed predictive mo...

In the last decennium, particle swarms have received considerable attention in the fields of optimization and control. Inspired by swarms of social animals, such as birds, fish, and termites, simple behavior on the local level has been shown to result in useful complex behavior on the global level. Particle Swarm Optimization has proven to be a very powerful optimization heuristic, and swarm ag...

Suitable solutions for multi-objective optimization problems are investigated as a set of solutions in the literature, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. The proposed algorithm in this paper is a hybrid of the particle swarm optimization algorithm [1] and a random search technique with quadratic approximation formula[2] n...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

the simultaneous optimization of multiple responses is an important problem in the design of industrial processes in order to achieve improved quality. in this paper, we present a new metaheuristic approach including simulated annealing and particle swarm optimization to optimize all responses simultaneously. for the purpose of illustration and comparison, the proposed approach is applied to tw...

in this work, by using the particle swarm optimization the electron raman scattering for square double quantum wells is optimized. for this purpose, by combining the particle swarm algorithm together with the numerical solution procedures for equations, and also the perturbation theory we find the optimal structure that maximizes the electron raman scattering. application of this algorithm to t...

in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...