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首页> 外文期刊>BioTechnology: An Indian Journal >Emergency supplies scheduling model for single demand point and its constrained multi-objective particle swarm optimization algorithm
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Emergency supplies scheduling model for single demand point and its constrained multi-objective particle swarm optimization algorithm

机译：单需求点应急物资调度模型及其约束多目标粒子群优化算法

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摘要

Aiming at the shortest emergency rescue completion time and the maximum mean fullload ratio of transportation, a newly multi-objective model of emergency supplies scheduling for single demand point is proposed. Through the analysis of the diversity, the finiteness, the maximum load and the maximum capacity of transportation, the suggested model is more comprehensive and realistic. In order to solve this model, a constrained multi-objective particle swarm optimization algorithm fused with multiple constraint handling techniques (CMOPSO-MCHT) is presented, in which integral iteration, nonnegative solution space limitation and hyper-plane constraints are constructed to update the velocity of each particle, a dynamic threshold constraint dominance rule is put forward to update the individual best location of each particle and a method of objective function modification is applied to update the global best location of the swarm. The results of numerical experiment show that the set of Pareto optimal solutions obtained by CMOPSO-MCHT has a much better convergence and spread.
机译：针对最短的应急救援完成时间和最大的运输平均满载率，提出了一种新的多目标单需求点应急物资调度模型。通过对多样性，有限性，最大负荷和最大运输能力的分析，所提出的模型更加全面和现实。为了求解该模型，提出了一种融合了多约束处理技术的约束多目标粒子群优化算法（CMOPSO-MCHT），构造了积分迭代，非负解空间限制和超平面约束来更新速度。针对每个粒子，提出了动态阈值约束优势规则，以更新每个粒子的个体最佳位置，并采用目标函数修正的方法来更新群的全局最佳位置。数值实验结果表明，通过CMOPSO-MCHT得到的一组Pareto最优解具有更好的收敛性和扩展性。

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