启发式随机搜索策略和局部优化算法相结合的求解方案是解决复杂函数优化的有效途径。
Combining a heuristic random searching strategy with local optimal algorithms is effective solution for complex optimization problem.
该算法采用新的启发式变异算子和局部搜索算子。
Heuristics mutation operator and local search scheme are designed in the algorithm.
该算法利用问题的邻域知识指导局部搜索，可克服元启发式算法随机性引起的盲目搜索。
The proposed algorithm utilizes neighborhood knowledge to direct its local search procedure which can overcome the blindness or randomness introduced by meta-heuristics.
在改进的启发式群局部搜索的基础上 ，利用分枝剪枝法得到全局最优解 。
On the basis of improved heuristic cluster local search, branch and cut method is used to get the global optimal solution.
在改进的启发式群局部搜索的基础上 ，利用分枝剪枝法得到全局最优解 。
On the basis of improved heuristic cluster local search, branch and cut method is used to get the global optimal solution.
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