在大范围海洋环境中，应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。
Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using ant colony optimization (in shorts, ACO) algorithm.
目前对有约束非线性规划问题还没有通用的求全局最优解的算法。
Currently, there is no general algorithm to find the global optimal solution for the constrained non-linear programming problems.
对广泛应用于金融及经济等实际问题中的一类带有多乘积约束的线性规划问题提出一种全局优化算法。
In this paper a global optimization algorithm is proposed for some programming problem (p) with additional multiplicative constraints, which can be applied to finance and economics and so on.
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