Multiperiod stochastic programming for biomass supply chain design under spatiotemporal variability of feedstock supply

2022 ◽  
Author(s):  
Changqiang Guo ◽  
Hao Hu ◽  
Shaowen Wang ◽  
Luis F. Rodriguez ◽  
K.C. Ting ◽  
...  
Keyword(s):  
Supply Chain ◽  
Stochastic Programming ◽  
Supply Chain Design ◽  
Spatiotemporal Variability ◽  
Biomass Supply

scholarly journals Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions

2018 ◽  
Vol 6 ◽  
Author(s):  
Bhavna Sharma ◽  
Robin Clark ◽  
Michael R. Hilliard ◽  
Erin G. Webb
Keyword(s):  
Supply Chain ◽  
Simulation Modeling ◽  
Supply Chain Design ◽  
Biomass Supply

scholarly journals Reliable Biomass Supply Chain Design under Feedstock Seasonality and Probabilistic Facility Disruptions

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1895 ◽  
Author(s):  
Zhixue Liu ◽  
Shukun Wang ◽  
Yanfeng Ouyang
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Biomass Supply

An Overview of Current Models and Approaches to Biomass Supply Chain Design and Management

2018 ◽  
Vol 5 (2) ◽  
pp. 138-149 ◽  
Author(s):  
Emanuela Melis ◽  
Andrea Vincis ◽  
Pier F. Orrù
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Biomass Supply

A goal programming model for a sustainable biomass supply chain network

2018 ◽  
Vol 12 (1) ◽  
pp. 79-102 ◽  
Author(s):  
Konstantinos Petridis ◽  
Evangelos Grigoroudis ◽  
Garyfallos Arabatzis
Keyword(s):  
Supply Chain ◽  
Biomass Production ◽  
Goal Programming ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mathematical Framework ◽  
Content Type ◽  
Biomass Supply ◽  
Conflicting Objectives ◽  
Economic Criteria

Purpose The design of a biomass supply chain is a problem where multiple stakeholders with often conflicting objectives are involved. To accommodate the aspects stakeholder, the supply chain design should incorporate multiple objectives. In addition to the supply chain design, the management of energy from biomass is a demanding task, as the operation of production of biomass products needs to be aligned with the rest of the operations of the biomass supply chain. The purpose of the paper is to propose a mathematical framework for the optimal design of biomass supply chain. Design/methodology/approach An integrated mathematical framework that models biomass production, transportation and warehousing throughout the nodes of a biomass supply chain is presented. Owing to conflicting objectives, weights are imposed on each aspect, and a 0-1 weighted goal programming mixed-integer linear programming (WGP MILP) programming model is formulated and used for all possible weight representations under environmental, economic and social criteria. Findings The results of the study show that emphasis on the environmental aspect, expressed with high values in the environmental criterion, significantly reduces the level of CO2 emissions derived from the transportation of biomass through the various nodes of the supply chain. Environmental and economic criteria seem to be moving in the same direction for high weight values in the corresponding aspect. From the results, social criterion seems to move to the opposite direction from environmental and economic criteria. Originality/value An integrated mathematical framework is presented modeling biomass production, transportation and warehousing. To the best of the authors’ knowledge, such a model that integrates multiple objectives with supply chain design has not yet been published.

scholarly journals Advanced Methodologies for Biomass Supply Chain Planning

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 659 ◽  
Author(s):  
Duc ◽  
Nananukul
Keyword(s):  
Supply Chain ◽  
Renewable Energy ◽  
Stochastic Programming ◽  
Energy Resources ◽  
Chain Model ◽  
Renewable Energy Resources ◽  
Biomass Supply ◽  
Supply Chain Model ◽  
Simulation Based ◽  
Parameter Search

Renewable energy resources have received increasing attention due to environmental concerns. Biomass, one of the most important renewable energy resources, is abundant in agricultural-based countries. Typically, the biomass supply chain is large due to the huge amount of relevant data required for building the model. As a result, using a standard optimization package to determine the solution for the biomass supply chain model might not be practical. In this study, the focus is on developing and applying advanced methodologies that can be used to determine a solution for the biomass supply chain model efficiently. The decisions related to plant selection, and distribution of biomass from suppliers to plants require optimization. The methodologies considered in this research are based on stochastic programming, parameter search, and simulation-based optimization. Computational results and managerial insights based on case studies from different regions of Vietnam are provided. The results show that parameter search is suitable for small problems only, while stochastic programming is suitable for small and medium problems. For large problem, simulation-based optimization performs better when considering the quality of the solution and the run time, although, this method does not guarantee an optimal solution. It provides good solutions where the gaps to the optimal solutions are between 0.59% and 8.41%.

Biomass supply chain design and analysis: Basis, overview, modeling, challenges, and future

2013 ◽  
Vol 24 ◽  
pp. 608-627 ◽  
Author(s):  
B. Sharma ◽  
R.G. Ingalls ◽  
C.L. Jones ◽  
A. Khanchi
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Biomass Supply
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