Improved African buffalo optimisation algorithm for petroleum product supply chain management. (14th September 2020)

• Record Type: Journal Article
• Authors: Igiri, Chinwe Peace; Singh, Yudhveer; Bhargava, Deepshikha; Shikaa, Samuel
• Is Part Of: International journal of grid and utility computing. Volume 11:Number 6(2020)
• Page Start: 769
• Page End: 779
• Publication Date: 2020-09-14
• Subjects: supply chain network -- computational intelligence -- petroleum product scheduling -- bio-inspired algorithm -- swarm intelligence -- African buffalo optimisation algorithm -- chaotic African buffalo optimisation algorithm -- chaotic-Levy flight African buffalo optimisation algorithm; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

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.