Biomass supply chain network design: An optimization-oriented review and analysis

Ghaderi, Hossein; Pishvaee, Mir Saman; Moini, Alireza

doi:10.1016/j.indcrop.2016.09.027

Cited by 210 publications

(121 citation statements)

References 148 publications

Supporting

Mentioning

114

Contrasting

Unclassified

Order By: Relevance

“…In literature on the subject of Biofuel Supply Chain Network Design (BSCND) problem, various approached have been applied. These approaches are classified into three groups, including (1) mathematical programming, (2) multi-criteria decision-making, and (3) heuristic or metaheuristic approaches, among which mathematical programming is the most frequently-used approach [5]. Given the objective function, constraints, and decision variables, mathematical programming models can be categorized into three groups, including (1) linear programming (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…[16]) can be used for solving problems that have high computational complexity and reaching near optimal solutions in a short period of time. For more details about the approaches that have been used in BSCND problems, interested readers may consult with Ghaderi et al [5] that provides the readers with a comprehensive review on BSCND models. Due to the dynamic environment under which a biofuel supply chain operates, a considerable degree of uncertainty affects the strategic decisions [5].…”

Section: Introductionmentioning

confidence: 99%

“…For more details about the approaches that have been used in BSCND problems, interested readers may consult with Ghaderi et al [5] that provides the readers with a comprehensive review on BSCND models. Due to the dynamic environment under which a biofuel supply chain operates, a considerable degree of uncertainty affects the strategic decisions [5]. In general, supply chain network design models will not be reliable enough if the uncertainty of the problem is not handled.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

Babazadeh

Ghaderi

Pishvaee

2019

Computers & Chemical Engineering

Self Cite

View full text Add to dashboard Cite

This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total costs of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

Babazadeh

Ghaderi

Pishvaee

2019

Computers & Chemical Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…Also, the continuous rising of fossil fuels prices has triggered the interest in these sources of energy [2,3]. Among the available options, forest biomass has gained interest in the last years [1,[4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level

et al. 2017

View full text Add to dashboard Cite

Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach.

show abstract

“…Bioenergy production systems, as a part of the solution to this problem, have attracted much attention in recent years because they can be appropriated substitutes for the traditional energy production systems which are, in addition to being finite and nonrenewable, associated with environmental problems (Sathre, 2014;Hamid et al, 2016) as well. Plants have the unique ability to convert the incoming flux of solar energy, a renewable form of energy, into useful biomass, in the form of food, feed and fuel.…”

Section: Introductionmentioning

confidence: 99%

Recent Progresses on Industrialization of Sweet Sorghum at IMP

XiCun¹,

Li²,

Liu³

et al. 2017

JAS

View full text Add to dashboard Cite

Sweet sorghum [Sorghum bicolor (L.) Moench] is not only an efficient and highly productive bioenergy crop that may help alleviate potential food-fuel tension caused by over-reliance on corn grain ethanol because of its outstanding features, including large amounts of fermentable carbohydrates in its juice-rich stalks, drought-tolerance, saline-alkaline resistance but also has considerable potential as food, forage crop owing to the limited availability of arable land. In this review, we have provided a brief overview of the progress that has been made in sweet sorghum industrialization at IMP range from research motivation, breeding, planting scale to products development. A conclusion is drawn that sweet sorghum industry is a systematic project, involving many key points, such as breeding, planting, production process and products sale. From a strategic and sustainability point of view, sweet sorghum is one of the most promising plants, particularly for ethanol, silage and liquor production.

show abstract

Biomass supply chain network design: An optimization-oriented review and analysis

Cited by 210 publications

References 148 publications

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level

Recent Progresses on Industrialization of Sweet Sorghum at IMP

Contact Info

Product

Resources

About