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Dimensionality reduction applied to the simultaneous optimization of the economic and life cycle environmental performance of supply chains

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  • Kostin, Andrei
  • Guillén-Gosálbez, Gonzalo
  • Jiménez, Laureano

Abstract

The design and planning of more sustainable supply chains should take into account several impacts for a proper assessment of the environmental performance of the logistic activities. Unfortunately, minimizing several environmental objectives simultaneously leads to hard optimization problems. This paper presents a rigorous computational framework for solving complex multi-objective optimization (MOO) problems encountered in the optimization of logistic tasks under economic and environmental indicators. The key ingredient of our method is the use of an objective reduction algorithm that allows identifying redundant objectives that can be omitted while still preserving the problem structure to the extent possible. The advantages of our method are illustrated by means of two case studies that address the multi-objective optimization of supply chains that produce bioethanol and hydrogen for vehicle use.

Suggested Citation

  • Kostin, Andrei & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2015. "Dimensionality reduction applied to the simultaneous optimization of the economic and life cycle environmental performance of supply chains," International Journal of Production Economics, Elsevier, vol. 159(C), pages 223-232.
    • Handle: RePEc:eee:proeco:v:159:y:2015:i:c:p:223-232
    DOI: 10.1016/j.ijpe.2014.09.018
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    References listed on IDEAS

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    1. Frota Neto, J. Quariguasi & Bloemhof-Ruwaard, J.M. & van Nunen, J.A.E.E. & van Heck, E., 2008. "Designing and evaluating sustainable logistics networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 195-208, February.
    2. Dimo Brockhoff & Eckart Zitzler, 2010. "Automated Aggregation and Omission of Objectives for Tackling Many-Objective Problems," Lecture Notes in Economics and Mathematical Systems, in: Dylan Jones & Mehrdad Tamiz & Jana Ries (ed.), New Developments in Multiple Objective and Goal Programming, pages 81-102, Springer.
    3. Nguyen Thoai, 2012. "Criteria and dimension reduction of linear multiple criteria optimization problems," Journal of Global Optimization, Springer, vol. 52(3), pages 499-508, March.
    4. Vaskan, Pavel & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2012. "Multi-objective design of heat-exchanger networks considering several life cycle impacts using a rigorous MILP-based dimensionality reduction technique," Applied Energy, Elsevier, vol. 98(C), pages 149-161.
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    Cited by:

    1. Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2023. "Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 255(C).
    2. Chamari Pamoshika Jayarathna & Duzgun Agdas & Les Dawes & Tan Yigitcanlar, 2021. "Multi-Objective Optimization for Sustainable Supply Chain and Logistics: A Review," Sustainability, MDPI, vol. 13(24), pages 1-31, December.
    3. Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2022. "Reprint of: Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 250(C).
    4. Aleksander Banasik & Jacqueline M. Bloemhof-Ruwaard & Argyris Kanellopoulos & G. D. H. Claassen & Jack G. A. J. Vorst, 2018. "Multi-criteria decision making approaches for green supply chains: a review," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 366-396, September.
    5. Barbosa-Póvoa, Ana Paula & da Silva, Cátia & Carvalho, Ana, 2018. "Opportunities and challenges in sustainable supply chain: An operations research perspective," European Journal of Operational Research, Elsevier, vol. 268(2), pages 399-431.

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