The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each part...

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

State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW) usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and th...

To solve the problems of low precision, slow convergence speed and difficult data fusion of standard particle filtering algorithm, a new hybrid intelligent optimization algorithm applicable for data fusion is presented in this paper and will conduce to finding the ideal solution domain by making use of the global convergence of artificial fish swarm and enhancement of fusion precision by guidin...

Robust optimization over time can effectively solve the problem of frequent solution switching in dynamic environments. In order to improve search performance robust algorithm, a particle swarm algorithm based on hybrid strategy (HS-DRPSO) is proposed this paper. Based optimization, HS-DRPSO combines differential evolution and brainstorms an ability. Moreover, selection employed realize differe...

Recently, Particle Swarm Optimization (PSO) algorithm has exhibited good performance across a wide range of application problems. A quick review of the literature reveals that research for solving the Quadratic Assignment Problem (QAP) using PSO approach has not much been investigated. In this paper, we design a hybrid meta-heuristic fuzzy scheme, called as variable neighborhood fuzzy particle ...

This paper proposes a hybrid Particle Swarm Optimization (PSO) method, which is based on the fusion of the PSO, Clonal Selection Algorithm (CSA), and Mind Evolutionary Computation (MEC). The clone function borrowed from the CSA and MEC-characterized similartaxis and dissimilation operations are embedded in the original PSO algorithm. Simulations of nonlinear function optimization are made to co...

This paper presents a hybrid differential evolution, particle swarm optimization and fuzzy c-means clustering algorithm called DEPSO-FCM for image segmentation. By the use of the differential evolution (DE) algorithm and particle swarm optimization to solve the FCM image segmentation influenced by the initial cluster centers and easily into a local optimum. Empirical results show that the propo...

Solving linear variational inequality by traditional numerical iterative algorithm not only can not satisfy parallel, but also its precision has much relationship with initial values. In this paper, a novel hybrid coevolutionary particle swarm optimization is used to solve linear variational inequality, which sufficiently exerts the advantage of particle swarm optimization such as group search,...