Designing a reliable bio-fuel supply chain network considering link failure probabilities

Poudel, Sushil; Marufuzzaman, Mohammad; Bian, Linkan

doi:10.1016/j.cie.2015.11.002

Cited by 67 publications

(21 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Alhaj et al [ 10 ] analyze the joint location-inventory problem and apply it to reduce carbon emission. There exist other influential studies considering similar settings to reduce carbon emission via typical operations strategies adjustment [ 2 , 11 , 12 , 13 ]. Some extant research investigates the way of reducing carbon emission in energy and bio-fuel supply chains [ 14 , 15 , 16 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Managing Risk Aversion for Low-Carbon Supply Chains with Emission Abatement Outsourcing

Wang

2018

IJERPH

View full text Add to dashboard Cite

Reducing carbon emissions, including emission abatement outsourcing at the supply-chain level, is becoming a significant but challenging problem in practice. Confronting this challenge, we therefore break down the practice to focus on a low-carbon supply chain consisting of one supplier, one manufacturer and one third-party emission-reducing contractor. The contractor offers a carbon reduction service to the manufacturer. In view of the increasing proportion of Greenhouse Gases (GHG) emissions and absence of carbon reduction policies in developing countries, we adopt the prospect of consumers’ low-carbon preferences to capture the demand sensitivity on carbon emission. By exploiting the Mean-Variance (MV) model, we develop a supply chain game model considering risk aversion. Comparing the supply chain performances of the cases under risk neutrality and risk aversion, we investigate the impact of the risk aversion of the supplier and the manufacturer on the low-carbon supply chain performances, respectively. We show that the risk aversion of chain members will not influence the relationship underlain by the profit-sharing contract between the manufacturer and contractor, whereas they may extend the supplier’s concerning range. Although the manufacturer’s risk aversion has a positive impact on the wholesale price, interestingly, the supplier’s impact on the wholesale price is negative. Furthermore, we propose a contract to coordinate the risk-averse low-carbon supply chain by tuning the aversion levels of the supplier and the manufacturer, respectively. Through numerical study, we draw on managerial insights for industrial practitioners to adopt a low carbon strategy potentially by managing the risk attitudes along the supply chain channel.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Managing Risk Aversion for Low-Carbon Supply Chains with Emission Abatement Outsourcing

Wang

2018

IJERPH

View full text Add to dashboard Cite

show abstract

“…Marufuzzaman et al [46] and Marufuzzaman and Eksioglu [47] proposed an optimization model to examine the impact of disruption risks at multi-modal facilities and biorefineries in a biofuel supply chain network. Poudel et al [48] proposed a pre-disaster planning model while considering the failure probability of links between multi-modal facilities. Bai et al [49] investigated the impact of failure risks at biorefineries and at intermediate transportation hubs in the biofuel supply chain network.…”

Section: Introductionmentioning

confidence: 99%

Designing a Reliable and Congested Multi-Modal Facility Location Problem for Biofuel Supply Chain Network

et al. 2018

Self Cite

View full text Add to dashboard Cite

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system while site-dependent facility failure and congestion are taken into consideration. The proposed model locates the multi-modal facilities and biorefineries and determines the optimal production, storage, and routing plans in such a way that the overall system cost is minimized. We propose a hybrid Constraint generation-based Rolling horizon algorithm to solve this challenging N P-hard problem. The performance of this algorithm is tested in a example case study with numerical analysis showing that the hybrid algorithm can find near-optimal solutions to large-scale problem instances in a reasonable amount of time. Results indicate that the effect of congestion reduces the usage of multi-modal facilities in the biofuel supply chain network while bio-refineries and multi-modal facilities tend to move away from coastal areas when disruption probabilities are taken into consideration.

show abstract

“…Khoshahval et al developed a new parallel optimization algorithm, P-PSOSA, in order to gain the possible minimum fitness value for the loading pattern optimization operation during suitable consuming runtime [11]. Poudel et al developed a generalized Benders decomposition algorithm seeking to strengthen a bio-fuel supply chain system's multi-modal facility links while accounting for limited budget availability [12]. Li et al proposed an inexact coal blending model based on the combination of interval programming and fuzzy linear programming, the model could help decision makers identify the optimal power coal blending schemes for the different boilers under four pollutants removal policy scenarios [13].…”

Section: Introductionmentioning

confidence: 99%

Development of a fuel management model for a multi-source district heating system under multi-uncertainty and multi-dimensional constraints

Zhuang

Gui

et al. 2017

Energy Conversion and Management

View full text Add to dashboard Cite

Designing a reliable bio-fuel supply chain network considering link failure probabilities

Cited by 67 publications

References 44 publications

Managing Risk Aversion for Low-Carbon Supply Chains with Emission Abatement Outsourcing

Managing Risk Aversion for Low-Carbon Supply Chains with Emission Abatement Outsourcing

Designing a Reliable and Congested Multi-Modal Facility Location Problem for Biofuel Supply Chain Network

Development of a fuel management model for a multi-source district heating system under multi-uncertainty and multi-dimensional constraints

Contact Info

Product

Resources

About