A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem
Recently, ‘greenness’ has become a very much needed condition in the transportation industry. In this study we develop a ‘green’, transshipment-enabled model for the Inventory Routing Problem (IRP), in a many-to-one distribution network where demand for each product is realistically assumed to be un...
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| Veröffentlicht in: | International journal of production economics Jg. 209; S. 381 - 398 |
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Elsevier B.V
01.03.2019
Elsevier [1991-....] |
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| Abstract | Recently, ‘greenness’ has become a very much needed condition in the transportation industry. In this study we develop a ‘green’, transshipment-enabled model for the Inventory Routing Problem (IRP), in a many-to-one distribution network where demand for each product is realistically assumed to be uncertain. The proposed framework is a bi-objective stochastic programming model. The first objective function aims to minimize the expected value of the supply chain costs including inevitable shortage costs. The second objective function aims to minimize the total quantity of the greenhouse gas (GHG) emission produced by the vehicles and disposed products. We introduce a very practical innovative application of transshipment option to control transportation cost, reduce GHG emissions and absorb the uncertainty. In order to solve the proposed model an efficient hybrid algorithm combining L-shaped method (a sort of decomposition approach for stochastic optimization) and compromise programming (a well-known approach for multi-objective optimization) is proposed. The results show that how companies can make a reasonable tradeoff between the cost and environmental concerns and emphasize the role of transshipment option as a lever to improve both economic and environmental performance and absorb the demand fluctuations. |
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| AbstractList | Recently, 'greenness' has become a very much needed condition in the transportation industry. In this study we develop a 'green', transshipment-enabled model for the Inventory Routing Problem (IRP), in a many-to-one distribution network where demand for each product is realistically assumed to be uncertain. The proposed framework is a bi-objective stochastic programming model. The first objective function aims to minimize the expected value of the supply chain costs including inevitable shortage costs. The second objective function aims to minimize the total quantity of the greenhouse gas (GHG) emission produced by the vehicles and disposed products. We introduce a very practical innovative application of transshipment option to control transportation cost, reduce GHG emissions and absorb the uncertainty. In order to solve the proposed model an efficient hybrid algorithm combining L-shaped method (a sort of decomposition approach for stochastic optimization) and compromise programming (a well-known approach for multi-objective optimization) is proposed. The results show that how companies can make a reasonable tradeoff between the cost and environmental concerns and emphasize the role of transshipment option as a lever to improve both economic and environmental performance and absorb the demand fluctuations. © 2017. Recently, ‘greenness’ has become a very much needed condition in the transportation industry. In this study we develop a ‘green’, transshipment-enabled model for the Inventory Routing Problem (IRP), in a many-to-one distribution network where demand for each product is realistically assumed to be uncertain. The proposed framework is a bi-objective stochastic programming model. The first objective function aims to minimize the expected value of the supply chain costs including inevitable shortage costs. The second objective function aims to minimize the total quantity of the greenhouse gas (GHG) emission produced by the vehicles and disposed products. We introduce a very practical innovative application of transshipment option to control transportation cost, reduce GHG emissions and absorb the uncertainty. In order to solve the proposed model an efficient hybrid algorithm combining L-shaped method (a sort of decomposition approach for stochastic optimization) and compromise programming (a well-known approach for multi-objective optimization) is proposed. The results show that how companies can make a reasonable tradeoff between the cost and environmental concerns and emphasize the role of transshipment option as a lever to improve both economic and environmental performance and absorb the demand fluctuations. |
| Author | Mohammadi Hoseinhajlou, Ebrahim Rekik, Yacine Mirzapour Al-e-hashem, Seyed M.J. |
| Author_xml | – sequence: 1 givenname: Seyed M.J. surname: Mirzapour Al-e-hashem fullname: Mirzapour Al-e-hashem, Seyed M.J. email: mirzapour@aut.ac.ir organization: ESC Rennes School of Business, 2 rue Robert D'Arbrissel, 35065, Rennes, France – sequence: 2 givenname: Yacine surname: Rekik fullname: Rekik, Yacine email: rekik@em-lyon.com organization: EMLYON Business School, DISP Lab, 23 avenue Guy de Collongue, 69134, Ecully, France – sequence: 3 givenname: Ebrahim surname: Mohammadi Hoseinhajlou fullname: Mohammadi Hoseinhajlou, Ebrahim email: e.mohamadi.ie@gmail.com organization: Department of Industrial Engineering, Iran University of Science & Technology, Iran |
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| Keywords | Inventory routing problem Hybrid L-shaped method Uncertain demand Transshipment Green supply chain Stochastic programming |
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| Snippet | Recently, ‘greenness’ has become a very much needed condition in the transportation industry. In this study we develop a ‘green’, transshipment-enabled model... Recently, 'greenness' has become a very much needed condition in the transportation industry. In this study we develop a 'green', transshipment-enabled model... |
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| SubjectTerms | Computer Science Green supply chain Hybrid L-shaped method Inventory routing problem Operations Research Stochastic programming Transshipment Uncertain demand |
| Title | A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem |
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