Sustainable cold supply chain management under demand uncertainty and carbon tax regulation

Babagolzadeh, Mahla and Shrestha, Anup ORCID: https://orcid.org/0000-0002-2952-0072 and Abbasi, Babak and Zhang, Yahua ORCID: https://orcid.org/0000-0003-1522-3402 and Woodhead, Alice and Zhang, Anming (2020) Sustainable cold supply chain management under demand uncertainty and carbon tax regulation. Transportation Research Part D: Transport and Environment, 80 (Article 102245). ISSN 1361-9209


Abstract

Increasing awareness of sustainability in supply chain management has prompted organizations and individuals to consider environmental impacts when managing supply chains. The issues concerning environmental impacts are significant in cold supply chains due to substantial carbon emissions from storage and distribution of temperature-sensitive product. This paper investigates the impact of carbon emissions arising from storage and transportation in the cold supply chain in the presence of carbon tax regulation, and under uncertain demand. A two-stage stochastic programming model is developed to determine optimal replenishment policies and transporta- tion schedules to minimize both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The performance and robustness of the matheuristic algo- rithm are analyzed using test instances in various sizes. A real-world case study in Queensland, Australia is used to demonstrate the application of the model. The results highlight that higher emissions price does not always contribute to the efficiency of the cold supply chain system. Furthermore, the analyses indicate that using heterogeneous fleet including light duty and medium duty vehicles can lead to further cost saving and emissions reduction.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Commerce (1 July 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Management and Enterprise (1 July 2013 -)
Date Deposited: 12 Feb 2020 05:22
Last Modified: 08 May 2020 02:39
Uncontrolled Keywords: sustainable cold supply chain; two-stage stochastic programming; carbon tax regulations; demand uncertainty; matheuristic algorithm
Fields of Research : 15 Commerce, Management, Tourism and Services > 1507 Transportation and Freight Services > 150703 Road Transportation and Freight Services
08 Information and Computing Sciences > 0806 Information Systems > 080605 Decision Support and Group Support Systems
01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010303 Optimisation
Identification Number or DOI: 10.1016/j.trd.2020.102245
URI: http://eprints.usq.edu.au/id/eprint/37986

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