摘要
给出的粒子群优化算法是一种群智能优化技术,利用群体和个体的智能行为来求解组合优化问题,并将多目标问题分别在粒子的各子种群中以内在并行的方式搜索多个非劣解,同时对各子种群粒子的适应度采用积分排序,较好地解决了电梯群控系统的多目标问题。充分弥补了传统方法解决多目标问题出现的不足。针对不同客流强度进行分析,分别得到不同平均的候梯时间和乘梯时间,结果表明采用此种改进的粒子群算法充分保证了算法的收敛速度和精度。
This paper deals with particle swarm optimization, a group intelligent optimization, which takes advantage of the intelligent behavior of the group and the particles to solve combinatorial optimization problems and has solved the multi-objective problem for elevator group control system through searching the non-inferior solutions parallel in the subgroups of the particles by integral method for sequencing according to the fitness of the particls in every subgroup to solve multi-objective problem. Diffewrent passenger intensities are analyzed in this paper and the results show that this improved particle swarm optinization can greatly improve the convergence speed and the precision.
出处
《渤海大学学报（自然科学版）》
CAS
2007年第1期42-45,共4页
Journal of Bohai University:Natural Science Edition
关键词
粒子群算法
多目标
电梯系统优化
群控
particle swarm optimization
multi-objective
optimization for elevator group controlsystem
group control
