1.Collaborative Optimization (CO), originated from the Compatibility Constrained Optimizaiton (CCO), is a bi-level optimization algorithm based on system decomposition and coordination. In CO, when come to a certain subsystem optimization, the influences from other subsystems are ignored temporarily, while a set of local variables take their places in the subsystem design.
协作优化算法（Collaborative Optimizaiton，简称CO）是在一致性约束优化算法（Compatibility Constrained Optimization，简称CCO）的基础上发展起来的，基于分解和协调的一种双层优化算法。
2.Basing on the background of Thermal Protection System (TPS) and MEMS designing, this thesis focused on the theoretical and numerical study of 3D continuum topology optimization of thermal-structural coupled system by adopting the Evolutionary Structural Optimization (ESO) method.
本文以热防护系统(Thermal ProtectionSystem,TPS)以及MEMS的设计为工程背景,采用了渐进结构优化(EvolutionaryStructural Optimization,ESO)方法,研究连续体热传导—结构耦合系统拓扑优化设计的理论和数值方法。 。
3.Collaborative reliability analysis method under multidisciplinary structure and a new reliability based MDO approach are proposed aimed to the requirement of efficiency, applicable of reliability based MDO. The former inherits advancements of CO, and has accurate, efficient computation because of employing simulated annealing algorithmic in system level and response surface instead disciplinary optimization.
并针对基于可靠性的多学科设计优化的高效适用的要求,提出了多学科结构下的协同可靠性分析方法和一种新的基于可靠性的多学科设计优化方法(RBMDO-SORA: Reliability Based Multidisciplinary Design Optimization-Sequential Optimization and Reliability Assessment)。
4.Breaking through the limit of BPR (Bussiness Process Reengineering), the author discusses the relationship of BPM and ERP and the application model of the implementation of BPM during ERP implementation with the view of the BPM (Bussiness Process Management, including BPO (Bussiness Process Optimization), BPI (Bussiness Process Improvement), BPR). The necessity of the BPM implementation is also briefly discussed on the platform of ERP system.
本文突破BPR(Bussiness Process Reengineering)的局限,从BPM(包括BPO (Bussiness Process Optimization), BPI (Bussiness Process Improvement),BPR)这个更宽广的视角出发，探讨BPM与ERP实施的辩证关系及其在ERP实施中的应用模式，并简要探讨了ERP系统上的BPM及其必要性。
5.Particle Swarm Optimization roots in research on colony movement of bird and fish. It is a kind of evolutive calculational methods based on group brainpower.
粒子群优化算法(Particle Swarm Optimization，PSO算法)源于鸟群和鱼群群体运动行为的研究，是一种基于群智能方法的演化计算技术，是演化计算领域中的一个新的分支。
6.The Optimization of The Ecological Economic Development for the Upper Reaches of the Yangtze River(Changjiang)
The Optimization of The Ecological Economic Development for the Upper Reaches of the Yangtze River（Changjiang）
7.Particle swarm optimization (PSO) is an evolutionary computation technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling.
粒子群优化算法(Particle Swarm Optimization，PSO算法)源于鸟群和鱼群群体运动行为的研究，是一种新的群体智能优化算法，是演化计算领域中的一个新的分支。
8.In order to adapt to the characteristics of multi-constrained quality of service(QoS) routing in next generation internet(NGI),an intelligent QoS unicast routing algorithm based on PSO(particle swarm optimization) is presented.
为了适应下一代互联网对多个约束条件服务质量(QoS)的要求,提出了一种基于粒子群优化PSO(Par-ticle Swarm Optimization)的智能QoS单播路由算法.
9.1. Ant Colony Optimization algorithm(ACO)has the limitations of poor convergence, and is easy to fall in local optima.
1.针对蚁群优化算法(Ant Colony Optimization, ACO)收敛速度慢、易陷于局部最优解的缺点,提出了一种基于协同进化思想的蚁群算法,用于求解TSP问题.
10.Particle Swarm Optimization was firstly proposed by Kennedy and Eberhart in 1995, and it is an evolutionary algorithm based on iterations.
粒子群优化算（Particle Swarm Optimization，简称PSO）首先由Kennedy和Eberhart于1995年提出，是一种基于迭代的进化计算的算法。
