石油产品供应链管理中改进的非洲水牛优化算法

Chinwe Peace Igiri, Yudhveer Singh, D. Bhargava, S. Shikaa
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引用次数: 4

摘要

现实世界的供应链网络由于问题规模大、约束条件多而复杂。石油产品的最优调度不仅会影响配送成本,而且会导致最优的产品调度。生物启发的方法是精确算法的优选替代方案,因为它不像后者那样需要初始解的先验知识。该研究提出了一种改进的非洲水牛优化(ABO)算法用于石油供应链分配。ABO是一种基于群体智能的生物启发算法,具有显著的性能跟踪记录。它模拟了大草原上非洲水牛的放牧和防御生活方式。混沌ABO和混沌-列维ABO是近年来研究中表现突出的ABO改进型。本研究应用标准ABO及其改进变体,得到了石油分配调度的近似最优解。对比结果表明,该方法优于现有的精确算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved African buffalo optimisation algorithm for petroleum product supply chain management
Real-world supply chain network is complex due to large problem size and constraints. An optimum petroleum products scheduling would not only influence the distribution cost but also result in optimal product scheduling. The bio-inspired method is preferred alternative to exact algorithms because it does not require prior knowledge of the initial solution unlike the latter. The study proposes an improved African Buffalo Optimisation (ABO) algorithm for petroleum supply chain distribution. The ABO is a swarm intelligence-based bio-inspired algorithm with significant performance track record. It models the grazing and defending lifestyle of the African buffaloes in the savannah. The chaotic ABO and chaotic-Levy ABO are the ABO's improved variants with outstanding performance in recent studies. The present study applies the standard ABO and its improved variants to obtain a near optimum petroleum distribution scheduling solution. The comparative result shows that the proposed approach outperformed existing exact algorithms.
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