The essential of planar location issue is nonlinear continuous function optimization under constrained condition.
平面选址问题实质上是带约束的非线性连续函数优化问题。
For function optimization problems, according to the nature of the objective function domain, can be divided into discrete function optimization and continuous function optimization.
对于函数优化这个问题，根据目标函数定义域的性质，可以分为离散函数最优化和连续函数最优化。
Particle swarm optimization is widely used to solve continuous function optimization issue, but its application in discrete combination optimization problems is still relatively few.
粒子群算法在求解连续函数优化问题中取得了广泛的应用，但是其在离散的组合优化问题中的运用还比较少。
Puts forward a new ACA based on grid division to overcome the weakness of ACA in solving continuous function optimization problem, and expands the discrete space to the continuous space.
针对蚁群算法在求解连续优化问题上相对较弱的特点，提出了基于网格划分的蚁群算法，将传统的用于求解离散空间优化问题的蚁群算法进行了扩展。
An adaptive ant colony algorithm is presented for the optimization of multi-minimum continuous function.
针对多极值连续函数优化问题，提出了一种自适应蚁群算法。
The classical Particle swarm optimization (PSO) algorithm is a powerful method to find the minimum of a numerical function, on a continuous definition domain.
经典的粒子群优化算法是一个在连续的定义域内搜索数值函数极值的很有效的方法。
Particle Swarm Optimization (PSO) algorithm is a powerful method to find the extremum of a continuous numerical function.
微粒群优化算法是求解连续函数极值的一个有效方法。
Particle Swarm Optimization (PSO) algorithm is a powerful method to find the extremum of a continuous numerical function.
微粒群优化算法是求解连续函数极值的一个有效方法。
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