Referring to immune optimization mechanism, an artificial immune system for time-varied functions optimization is presented.
借鉴生物免疫系统优化机理，构造一种人工免疫系统，用于求解时变函数优化问题。
In this paper, an optimization algorithm for time-varied functions optimization referring to immune optimization mechanism is presented.
论文借鉴免疫反应机理，提出一种用于求解动态环境下函数优化问题的免疫算法。
The cell area subject to cell capacity is expounded, the framework of immune optimization algorithm is given, and simulation experiments are done to validate algorithm.
研究了容量约束下的小区面积，给出了免疫优化算法框架，并与文献算法进行了对比实验。
Based on biologic immune system, this paper summarizes the bionics mechanism of immune optimization, while clonal selection and immune network theories are discussed detailedly.
本文以生物免疫系统为基础，概述免疫优化的仿生机理，重点介绍了克隆选择和免疫网络理论。
Immune algorithm is a completely new method band together with the principle of life-form evolution, optimization technique and computer technique.
免疫算法是一种生物进化原理、最优化技术和计算机技术相结合的全新算法。
Immune algorithm is a kind of intelligent optimization algorithm which simulates the biology immunity system, and has potential to provide novel method for solving problem.
免疫算法是模拟生物免疫系统功能的一种智能优化算法，具有解决复杂工程问题的潜力。
An improved immune algorithm is put forward and applied for nonlinear optimization in cellular wireless location.
本文提出了一种改进的免疫算法，对蜂窝网络无线定位估计中的非线性优化问题进行求解。
The research of the Parallel Immune Algorithm application will help to solve other combinatorial optimization problems.
并行免疫算法的应用研究将有助于其他组合优化问题的解决。
Immune algorithm is an optimization algorithm based on immune system of organism in nature, now it is a new development direction in multi-object of mechanical optimization design.
免疫算法是一种基于自然界生物体免疫系统的优化算法，是目前机械多目标优化设计中的一个新的研究方向。
Immune algorithm has been successful in many fields, such as virus removal and invasive monitoring, function optimization, TSP problem, data analysis and mining, fault diagnosis.
免疫算法已在很多领域得到了成功的应用，如病毒清除和入侵监控、函数优化、TSP问题、数据分析和挖掘、故障诊断等。
By simulating the antibody search mechanism, and combining the immune network theory, a new immune learning algorithm for multi-modal function optimization was presented.
模拟抗体搜索机制，结合免疫网络理论，提出一种新的优化算法。
In order to solve NP - shop scheduling combinatorial optimization problems, an immune forgotten algorithm for job shop scheduling is proposed.
为了解决车间调度NP组合优化的难题，提出了基于免疫遗忘的车间调度算法。
Immune evolutionary algorithm is a new optimization algorithm inspired by biological immune mechanism based on the deep understanding of the existing evolutionary algorithm.
免疫进化算法是在深入理解现有进化算法的基础上，受生物免疫机制的启发而形成的一种新的优化算法。
In this paper, an immune clustering algorithm is presented, which includes antibody production, antigen recognition, and antibody optimization.
提出了一种免疫聚类算法，该算法主要包括抗体产生、抗原识别和抗体优化等过程。
In solving global optimization, immune algorithm is usually weak in local search, while evolutionary diffusion optimization is weak in global search.
在求解全局优化问题时，通常免疫算法、进化扩散算法分别在局部搜索和全局搜索方面表现较弱。
To solve complex constrained optimization problems, we propose a new immune-genetic algorithm.
提出一种新的求解复杂约束优化问题的免疫遗传算法。
Referred to the character of particle swarm optimization and immune network theory, an immune particle swarm network algorithm for multimodal function optimization is proposed.
针对多峰函数优化问题，借鉴粒子群优化特性和免疫网络理论，提出一种免疫粒子群网络算法。
To address the optimization problem, a modified artificial immune algorithm was developed.
针对这一优化问题，设计了一种人工免疫算法。
An example was tested and showed immune algorithm has good searching performance, and it is efficient for solving unit commitment problem compared with other optimization algorithms.
经实例验证表明，优化免疫算法具有良好的搜索性能，是解决机组优化组合问题的有效方法。
A parallel optimization algorithm is proposed based on the idea of affinity maturation of immune cells in the germinal centers in order to achieve as many as possible local optimal solutions.
为此 ，研究了产品与过程设计活动之间的并行度优化问题 ，并建立了数学模型 ，给出了求解该问题的算法 ，其目的是使因延迟产品开发完成时间和不必要的设计修改而带来的成本尽可能最低。
However, comparing with other intelligent algorithms, immune algorithm also owns some disadvantage, like premature convergence and poor ability in local optimization.
然而，类似于其它新型智能算法，人工免疫算法也存在一些不足，如存在早熟收敛、局部搜索能力不足等。
Introduce main problems of Constained Optimization and methods to solve them. Using immune computing algorithm for solving nonlinear programming problem.
介绍了约束条件的函数优化的主要问题及处理约束的解决方法，针对一般性非线性规划问题，采用免疫算法来进行处理。
Introduce main problems of Constained Optimization and methods to solve them. Using immune computing algorithm for solving nonlinear programming problem.
介绍了约束条件的函数优化的主要问题及处理约束的解决方法，针对一般性非线性规划问题，采用免疫算法来进行处理。
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