Bagley College of Engineering Publications and Scholarship

Abstract

The goal of this study is to recognise various factors for responsive SCs that affect supply risk and model their impact on SC design and operation. We propose a conceptual model for SC responsiveness that encompasses practices such as flexibility, agility, internal integration, and visibility. This conceptual model is utilised to build up a multi-objective, multi-period SC design and operation model. A heuristic algorithm is developed to find the supplier, product, period, and production rate for the numerical problem. The improved genetic algorithm (GA) produces solutions with more accuracy in considerably less time than a traditional GA. Finally, an approach to prioritise the objective functions is developed that allows managers to focus on specific objective functions more than optimum values. This approach provides risk-averse, responsiveness-oriented, cost-effective managers the capability to set priorities based on their policies.

Publisher

Taylor & Francis

First Page

1338

Last Page

1361

DOI

https://doi.org/10.1080/00207543.2019.1633024

Publication Date

1-1-2019

College

James Worth Bagley College of Engineering

Department

Department of Industrial and Systems Engineering

Keywords

supply chain, responsiveness, risk, genetic algorithm

Disciplines

Engineering

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