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多目标货物配装问题是一个复杂的组合优化问题,属于NP难问题,本文用混合粒子群算法求解多目标货物配装问题。混合粒子群算法在基本粒子群算法的基础上,通过引进遗传算法中的交叉和变异的策略,避免了陷入局部最优,加快了达到全局最优的收敛速度。此外,本文提出用权重系数来平衡各目标使各目标都能达到相对较优的效果。-Multi-objective loading of goods is a complicated combinatorial optimization problems are NP hard problems, this paper, hybrid particle swarm algorithm to solve multi-objective problem loading cargo. Hybrid Particle Swarm Algorithm in elementary particle swarm optimization based on genetic algorithm through the introduction of crossover and mutation of the strategy to avoid a fall into local optimum, global optimum to achieve accelerated convergence. In addition, this paper, the weight factor used to balance the various objectives so that the objectives can be achieved relatively better results.
Date : 2026-01-09 Size : 6kb User : 廖志

求解双层规划问题常用的算法有极点算法、直接搜索法、下降法和非数值优化方法(如模拟退火算法、遗传算法等),遗传算法的求解思路是:首先对上层的决策变量编码,代人下层规划模型,通过求解下层模型的决策变量值,代入上层模型计算适应度值,然后进行交叉、变异、选择操作,最后求出最优解。-Solving Bilevel Programming Problems with pole algorithm commonly used algorithms, direct search method, descent and non-numerical optimization methods (such as simulated annealing, genetic algorithms, etc.), genetic algorithm for solving approaches: the first on the top of the decision variable coding, on behalf of the were lower programming model, by solving the lower model of decision variables values into the upper model on behalf of the fitness value, and then crossover and mutation, select Options, and finally get the best solution.
Date : 2026-01-09 Size : 2kb User : 大海
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