Title: Hybrid meta-heuristic-based inventory management using block chain technology in cloud sector

Authors: Chinnaraj Govindasamy; Arokiasamy Antonidoss

Addresses: Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Padur, Chennai, India ' Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Padur, Chennai, India

Abstract: This paper plans to develop an inventory management model in the supply chain with cloud and block chain assistance. This paper considers the inventory management of a supply chain that involves multiple suppliers, manufacturers, and distributers. The data management is done by the block chain technology, where each distributer holds a hash function to store its data, which cannot be restored by the other distributers. The proposed model intends to reduce the multi-objective inventory cost involving transaction cost, inventory holding cost, shortage cost, transportation cost, and time cost. The hybridisation of two meta-heuristic algorithms like spider monkey optimisation (SMO) and sea lion optimisation (SLnO) termed as spider monkey local leader-based sea lion optimisation algorithm (SMLL-SLnO) is used to improve the inventory management model. Finally, the feasibility and effectiveness of the proposed optimisation model are validated by comparing over the other traditional models.

Keywords: inventory management; supply chain management; block chain technology; cloud computing; meta-heuristic algorithm; spider monkey local leader-based sea lion optimisation.

DOI: 10.1504/IJAHUC.2022.126110

International Journal of Ad Hoc and Ubiquitous Computing, 2022 Vol.41 No.3, pp.147 - 169

Received: 06 Nov 2020
Accepted: 01 Nov 2021
Published online: 11 Oct 2022 *

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