Title: Improved African buffalo optimisation algorithm for petroleum product supply chain management

Authors: Chinwe Peace Igiri; Yudhveer Singh; Deepshikha Bhargava; Samuel Shikaa

Addresses: Amity University, Rajasthan, India ' Amity University, Rajasthan, India ' University of Petroleum and Energy Studies, Dehradun, India ' Taraba State University, Jalingo, Nigeria

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.

Keywords: 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.

DOI: 10.1504/IJGUC.2020.110905

International Journal of Grid and Utility Computing, 2020 Vol.11 No.6, pp.769 - 779

Received: 05 Jun 2019
Accepted: 26 Sep 2019
Published online: 01 Nov 2020 *

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