Modeling of Green Supply Chain Logistics

Hsu, Hsin-Wei

doi:10.4018/978-1-60566-114-8.ch012

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…In this numerical example, they are assumed to be 10%. Hsu and Wang (2009) have carried out parameter analy- sis to obtain the ranges of land filling and recovery rates with the same optimal logistics pattern. Also, they pointed out that because of the recovery rate is more sensitive than the land filling rate, therefore, with a smaller tolerance range, any change of recovery rate should be given more attention in control and management.…”

Section: Numerical Examplementioning

confidence: 99%

A Closed-Loop Logistics Model for Green Supply Chain Management

Basiri

Shemshadi

Tarokh

2011

International Journal of Applied Logistics

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Recently, with the environmental crisis, Green supply chain management (or GSCM), and in particular closed loop supply chain model, has received considerable attention by researchers. Closed loop supply chain model aims at reduction of waste and generating profit for enterprises through integrating forward and reverse logistics. Unfortunately, there is limited research on general models for closed loop supply chains in literature. In this paper, extending and enhancing previous models, a general model is proposed for closed loop supply chains using linear programming. The goal of this study is to minimize the leakage of a closed loop supply chain to avoid waste and reduce SCM costs.

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Section: Numerical Examplementioning

confidence: 99%

A Closed-Loop Logistics Model for Green Supply Chain Management

Basiri

Shemshadi

Tarokh

2011

International Journal of Applied Logistics

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Sustainable closed-loop supply chain network design with discount supposition

Hajiaghaei–Keshteli

Fathollahi-Fard

2018

Neural Comput & Applic

126

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A possibilistic approach to the modeling and resolution of uncertain closed-loop logistics

Wang

Hsu

2012

Fuzzy Optim Decis Making

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Closed-loop logistics planning is an important tactic for the achievement of sustainable development. However, the correlation among the demand, recovery, and landfilling makes the estimation of their rates uncertain and difficult. Although the fuzzy numbers can present such kinds of overlapping phenomena, the conventional method of defuzzification using level-cut methods could result in the loss of information. To retain complete information, the possibilistic approach is adopted to obtain the possibilistic mean and mean square imprecision index (MSII) of the shortage and surplus for uncertain factors. By applying the possibilistic approach, a multi-objective, closed-loop logistics model considering shortage and surplus is formulated. The two objectives are to reduce both the total cost and the root MSII. Then, a non-dominated solution can be obtained to support decisions with lower perturbation and cost. Also, the information on prediction interval can be obtained from the possibilistic mean and root MSII to support the decisions in the uncertain environment. This problem is non-deterministic polynomial-time hard, so a new algorithm based on the spanning tree-based genetic algorithm has been developed. Numerical experiments have shown that the proposed algorithm can yield comparatively efficient and accurate results.

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Modeling of Green Supply Chain Logistics

Cited by 4 publications

References 7 publications

A Closed-Loop Logistics Model for Green Supply Chain Management

A Closed-Loop Logistics Model for Green Supply Chain Management

Sustainable closed-loop supply chain network design with discount supposition

A possibilistic approach to the modeling and resolution of uncertain closed-loop logistics

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