Managing convergence and diversity is essential in the design of multiobjective particle
swarm optimization (MOPSO) in search of an accurate and well distributed approximation of …

粒子群优化算法因形式简洁, 收敛快速和参数调节机制灵活等优点, 同时一次运行可得到多个解,
且能逼近非凸或不连续的Pareto 最优前端, 因而被认为是求解多目标优化问题最具潜力的方法 …

In recent years, many evolutionary algorithms and population-based algorithms have been
developed for solving multi-objective optimization problems. In this paper, the authors …

In view of the low efficiency of the particle swarm algorithm under multiple constraints of
reservoir optimal operation, this paper introduces a particle swarm algorithm based on …

A multi-objective optimization method for constant stress accelerated degradation test is
proposed in order to solve the problem of different or even conflicted test configuration under …

Abstract The Particle Swarm Optimization (PSO) algorithm was put forth by Kennedy and
Eberhart in the year 1995. It is widely known for the ease with which it can be implemented …

The tuning of a proportional-integral-derivative (PID) controller for hydraulic turbine
governing system is a constrained engineering problem. The PID control parameters must …

An optimisation is a process of finding maxima or minima of the objective function. Particle
Swarm Optimisation (PSO) is a nature-inspired, meta-heuristic, black box optimisation …