Big Data Analytics and Optimization Models for Intelligent Supply Chain and Operations Management: A Comprehensive Review

Abstract

BDA and optimization are two disruptions which have significantly contributed towards the development of SCOM under the domain of intelligent SCM, which is also known as Supply Chain 4.0. In this sense, this current review of literature aims to explore latest developments achieved in the area of BDA, together with optimization strategies to make intelligent decisions within SCOM operations. Specifically, based on a literature review as well as Delphi analysis, this current research provides a brief overview of diverse instances of BDA classified as descriptive, predictive, and prescriptive analysis, along with other forms of optimization methods like mathematical programming, heuristics, metaheuristics, and machine learning-based optimization techniques, among many others. It is evident that combination results in remarkable improvements in terms of accuracy, response rate, efficiency, sustainability, and resilience; nevertheless, some drawbacks continue to persist with regard to real-time implementation, management of unstructured data, validation, and academic/practitioner collaboration.