A multi-objective optimisation for green supply chain network design problem considering economic and environmental sustainability

被引:0
作者
Chhun S. [1 ]
Lekhavat S. [1 ]
Alghababsheh M. [2 ]
机构
[1] Faculty of Logistics, Burapha University, Chonburi
[2] Department of Business Management, School of Business, Mutah University, Alkarak
关键词
environmental sustainability; green supply chain; multi-commodity; multi-objective optimisation; particle swarm optimisation; supply chain network design problem;
D O I
10.1504/IJISE.2024.138159
中图分类号
学科分类号
摘要
The aim of this study is to develop a multi-objective optimisation for the green supply chain network design (GSCND) problem considering economic and environmental sustainability. The economic and environmental sustainability of different facilities (i.e., suppliers, plants and distribution centres) and allocation routes under five different scenarios of demand, capacity, distance, and area were evaluated. The economic sustainability was assessed in terms of four supply chain costs (i.e., establishment, transportation, production and holding costs). Environmental sustainability was measured using the ReCipe method – a method of life cycle assessment (LCA). The result revealed an interesting practical solution to the scenarios considered. Copyright © 2024 Inderscience Enterprises Ltd.
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收藏
页码:20 / 45
页数:25
相关论文
共 34 条
  • [1] Alghababsheh M., Gallear D., Social sustainability in the supply chain: a literature review of the adoption, approaches and (un) intended outcomes, Management & Sustainability: An Arab Review, 1, 1, pp. 84-109, (2022)
  • [2] Amin S.H., Zhang G., A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return, Applied Mathematical Modelling, 37, 6, pp. 4165-4176, (2013)
  • [3] Bamrungbutr C., Differential Evolution Algorithm for the Multicommodity Distribution Network Design Problem, (2011)
  • [4] Barbosa-Povoa A.P., Da Silva C., Carvalho A., Opportunities and challenges in sustainable supply chain: an operations research perspective, European Journal of Operational Research, 268, 2, pp. 399-431, (2018)
  • [5] Buritica N.C., Escobar J.W., Sanchez L.V.T., Designing a sustainable supply network by using mathematical programming: a case of fish industry, International Journal of Industrial and Systems Engineering, 27, 1, pp. 48-72, (2017)
  • [6] Chibeles-Martins N., Pinto-Varela T., Barbosa-Povoa A.P., Novais A.Q., A multi-objective meta-heuristic approach for the design and planning of green supply chains-MBSA, Expert Systems with Applications, 47, pp. 71-84, (2016)
  • [7] Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6, 2, pp. 182-197, (2002)
  • [8] Doherty S., Hoyle S., Supply chain decarbonization: the role of logistics and transport in reducing supply chain carbon emissions, (2009)
  • [9] Eldahamsheh M., Almomani H., Bani-Khaled A., Al-Quran A., Al-Hawary S., Mohammad A., Factors affecting digital marketing success in Jordan, International Journal of Entrepreneurship, 25, pp. 1-12, (2021)
  • [10] Eskandarpour M., Dejax P., Miemczyk J., Peton O., Sustainable supply chain network design: an optimization-oriented review, Omega, 54, pp. 11-32, (2015)