In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...

This paper presents a short study on the hybridization of a swarm based optimization algorithm with a single agent based algorithm. Swarm based algorithms and single agent based algorithms have each distinct advantages and disadvantages. One goal of the presented work is to combine the concepts of the two different algorithms such that a more effective optimization routine results. In particula...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Presented a new hybrid particle swarm algorithm based on P systems, through analyzing the working principle and improved strategy of the elementary particle swarm algorithm. Used the particles algorithm combined with the membrane to form a community, particles use wheel-type structure to communicate the current best particle within the community. The best particles, as Representative, compete f...

differential steering of in-wheel electric vehicle provides the functions of both active steering and power assisted steering with the coupling control of force and displacement transfer characteristic of system. a collaborative optimization model of the differential power-assisted steering system of in-wheel electric vehicle is built, with steering economy as the main system optimization goal,...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...