scholarly journals Machine-Learning Methods to Select Potential Depot Locations for the Supply Chain of Biomass Co-Firing

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6554
Author(s):  
Diana Goettsch ◽  
Krystel K. Castillo-Villar ◽  
Maria Aranguren
Keyword(s):  
United States ◽  
Machine Learning ◽  
Supply Chain ◽  
Ghg Emissions ◽  
The United States ◽  
Mixed Integer ◽  
Total Cost ◽  
Computational Burden ◽  
Milp Model

Coal is the second-largest source for electricity generation in the United States. However, the burning of coal produces dangerous gas emissions, such as carbon dioxide and Green House Gas (GHG) emissions. One alternative to decrease these emissions is biomass co-firing. To establish biomass as a viable option, the optimization of the biomass supply chain (BSC) is essential. Although most of the research conducted has focused on optimization models, the purpose of this paper is to incorporate machine-learning (ML) algorithms into a stochastic Mixed-Integer Linear Programming (MILP) model to select potential storage depot locations and improve the solution in two ways: by decreasing the total cost of the BSC and the computational burden. We consider the level of moisture and level of ash in the biomass from each parcel location, the average expected biomass yield, and the distance from each parcel to the closest power plant. The training labels (whether a potential depot location is beneficial or not) are obtained through the stochastic MILP model. Multiple ML algorithms are applied to a case study in the northeast area of the United States: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and Multi-Layer Perceptron (MLP) Neural Network. After applying the hybrid methodology combining ML and optimization, it is found that the MLP outperforms the other algorithms in terms of selecting potential depots that decrease the total cost of the BSC and the computational burden of the stochastic MILP model. The LR and the DT also perform well in terms of decreasing total cost.

scholarly journals Optimization of the Supply Chain in the Production of Ethanol from Agricultural Biomass Using Mixed-Integer Linear Programming (MILP): A Case Study

2020 ◽  
Vol 2020 ◽  
pp. 1-25 ◽  
Author(s):  
Edgar León-Olivares ◽  
Hertwin Minor-Popocatl ◽  
Omar Aguilar-Mejía ◽  
Diana Sánchez-Partida
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Raw Material ◽  
Mixed Integer ◽  
Study Region ◽  
Total Cost ◽  
Agricultural Biomass

The production of biofuels from agricultural biomass has attracted much attention from researchers in recent years. Biomass residues generated from agricultural production of corn and barley represent an essential source of raw material for the production of biofuels, and a mathematical programming-based approach can be used to establish an efficient supply chain. This paper proposes a model of mixed-integer linear programming (MILP) that seeks to minimize the total cost of the bioethanol supply chain. The proposal allows determining the optimal number and location of storage centers, biorefineries, and mixing plants, as well as the flow of biomass and bioethanol between the facilities. To show the proposed approach, we present a case study developed in the region of Tulancingo, Hidalgo, in Mexico (case study), considering the potential of biomass (corn and barley residues) in the region. The results show the costs for the production of bioethanol, transportation, and refining and total cost of the bioethanol supply chain, besides a sensitivity analysis on the costs of the bioethanol supply chain which is presented by mixing different percentages of bioethanol with fossil fuel to satisfy the demand. We conclude that the proposed approach is viable in the process of configuring the supply chain within the proposed study region.

scholarly journals A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran

2021 ◽  
Author(s):  
Mohammad Ehsan Zerafati ◽  
Ali Bozorgi-Amiri ◽  
Amir-Mohammad Golmohammadi ◽  
Fariborz Jolai
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Environmental Impacts ◽  
Deterministic Model ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Proposed Model ◽  
Milp Model

Abstract Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.

The Economics of Biomass Logistics and Conversion Facility Mobility: An Oregon Case Study

2018 ◽  
Vol 34 (1) ◽  
pp. 57-72 ◽  
Author(s):  
Michael David Berry ◽  
John Sessions
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Biomass Conversion ◽  
The United States ◽  
Mixed Integer ◽  
Modular System ◽  
Base Case ◽  
Biomass Availability ◽  
The Impact

Abstract. This article presents an analysis of transportable biomass conversion facilities to evaluate the conceptual and economic viability of a highly mobile and modular biomass conversion supply chain in the Pacific Northwest of the United States. The goal of this work is to support a broader effort to more effectively and sustainably use residual biomass from commercial harvesting operations that are currently piled and burned as part of site preparation. A structural representation is first developed to include sources of biomass feedstock, distributed preprocessing hubs (centralized landings), and centralized processing facilities (biomass to product conversion sites) to produce desired products and byproducts. A facility costing model was developed to evaluate potential economics of scale, which then informed the optimization study. A mixed integer linear programming model was developed to characterize, evaluate, and optimize biomass collection, extraction, logistics, and facility placement over a regional landscape from a strategic level to evaluate the mobility concept. The objective was to minimize supply chain operational costs in order to quantify financial advantages and identify challenges of the proposed system modularity and mobility. A Lakeview, Oregon case study was evaluated with an assumed modular biochar facility servicing the region. In particular, we review economies of scale, mobility, energy costs, and biomass availability tradeoffs. This analysis points towards a modular system design of movement frequency between 1 to 2 years being most viable in the conditions evaluated. It was found that the impact of plant movement, scale, and biomass availability can increase supply chain costs by $11/BDMT ($10/BDT), $33/BDMT ($30/BDT), and $22/BDMT ($20/BDT) above the base case cost of $182/BDMT ($165/BDT) for a large-scale facility [45,000 BDMT yr-1(50,000 BDT yr-1)]in the conditions evaluated. Additionally, potential energy cost savings of a non-mobile modular stationary site as compared to one which utilizes off-grid electrical powers about $11/BDMT ($10/BDT) for a biochar facility. From the cases evaluated, a large-scale plant with limited mobility would be preferred under low availability of biomass conditions, whereas a stationary grid-connected plant would be more cost effective under higher availability conditions. Results depend greatly on the region, assumed harvest schedule, biomass composition, and governing biomass plant assumptions. Keywords: Biomass products, Biomass supply, Facility location, Mixed integer programming, Strategic planning, Transportable plants.

Gendered differences in emigration and mobility perspectives among European researchers working abroad

2014 ◽  
Vol 7 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Elisabeth Scheibelhofer
Keyword(s):  
United States ◽  
Qualitative Research ◽  
Qualitative Study ◽  
Social Relations ◽  
The United States ◽  
Research Strategy ◽  
The Future ◽  
Highly Skilled

This paper focuses on gendered mobilities of highly skilled researchers working abroad. It is based on an empirical qualitative study that explored the mobility aspirations of Austrian scientists who were working in the United States at the time they were interviewed. Supported by a case study, the paper demonstrates how a qualitative research strategy including graphic drawings sketched by the interviewed persons can help us gain a better understanding of the gendered importance of social relations for the future mobility aspirations of scientists working abroad.

‘A Routh O’ Auld Nick-Nackets’ – the antiquarian collection of John Rae

2015 ◽  
Vol 36-37 (1) ◽  
pp. 163-183
Author(s):  
Paul Taylor
Keyword(s):  
United States ◽  
Nineteenth Century ◽  
Social Context ◽  
Moral Education ◽  
The United States ◽  
Representative Case ◽  
National Museums ◽  
The Individual ◽  
The University

John Rae, a Scottish antiquarian collector and spirit merchant, played a highly prominent role in the local natural history societies and exhibitions of nineteenth-century Aberdeen. While he modestly described his collection of archaeological lithics and other artefacts, principally drawn from Aberdeenshire but including some items from as far afield as the United States, as a mere ‘routh o’ auld nick-nackets' (abundance of old knick-knacks), a contemporary singled it out as ‘the best known in private hands' (Daily Free Press 4/5/91). After Rae's death, Glasgow Museums, National Museums Scotland, the University of Aberdeen Museum and the Pitt Rivers Museum in Oxford, as well as numerous individual private collectors, purchased items from the collection. Making use of historical and archive materials to explore the individual biography of Rae and his collection, this article examines how Rae's collecting and other antiquarian activities represent and mirror wider developments in both the ‘amateur’ antiquarianism carried out by Rae and his fellow collectors for reasons of self-improvement and moral education, and the ‘professional’ antiquarianism of the museums which purchased his artefacts. Considered in its wider nineteenth-century context, this is a representative case study of the early development of archaeology in the wider intellectual, scientific and social context of the era.

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