Analysis of the particle swarm algorithm in the optimization of a three-phase slurry catalytic reactor. Comput Chem Eng. 2011;35(12): 2741-2749.Analysis of the particle swarm algorithm in the optimization of a three-phase slurry catalytic reactor[J] . Adriano Pinto Mariano,Caliane Bastos Borba...
This paper describes the inverse design of the particle swarm optimization algorithm combined with the three-dimensional finite-difference time-domain simulation to design a waveguide crossing that resembles a binary code. The device consists of 15 × 15 air holes in a 220-nm silicon slab on a ...
The main steps of the PSO algorithm for the optimization of EE are shown below: Algorithm 1: Energy Efficiency Optimization. 1. Initialize the boundaries of M and K and the parameters NP, ND, ω, c1, c2 2. for each particle i 3. Initialize the velocity Vi and position Xi...
OptimizationThe generalized gamma distribution offers a highly flexible family of models for lifetime data and includes a considerable number of distributions as special cases. This work deals with the use of the particle swarm optimization (PSO) algorithm in the maximum likelihood estimation of ...
We present the maximum likelihood estimation (MLE) via particle swarm optimization (PSO) algorithm to estimate the mixture of two Weibull parameters with complete and multiple censored data. A simulation study is conducted to assess the performance of the MLE via PSO algorithm, quasi-Newton method ...
Hu W, Liang H, Peng C, Du B, Hu Q (2013) A hybrid chaos-particle swarm optimization algorithm for the vehicle routing problem with time window. Entropy 15(4):1247–1270. : 10.3390/e15041247 . http://www.mdpi.com/1099-4300/15/4/1247...
A novel particle-swarm optimization(PSO) algorithm which coordinates the exploration ability and the exploitation ability(EEPSO) is presented. This algorithm divides the population of the swarm into the evolutionary sub-swarm and the randomized sub-swarm. During the evolution, the randomized sub-swarm...
This paper focuses on the problem of robot rescue task allocation, in which multiple robots and a global optimal algorithm are employed to plan the rescue task allocation. Accordingly, a modified particle swarm optimization (PSO) algorithm, referred to as task allocation PSO (TAPSO), is proposed...
A particle swarm-based dynamic optimization algorithm is developed to solve the nonlinear model predictive differential game, affected by the uncertainties. A heuristic robust model predictive differential game guidance algorithm has not been given yet. The performance of the new guidance algorithm is ...
The proposed algorithm evaluates the losses and bus voltage of base condition. There is random generation of populations of solutions at first stage of particle swarm optimization method and then particle moves in search space and then find the best solution. It works with the objective that ...