Integrated Multimodal Transportation Model for a Switchgrass-Based Bioethanol Supply Chain: Case Study in North Dakota

2017 ◽  
Vol 2628 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Yong Shin Park ◽  
Joseph Szmerekovsky ◽  
Atif Osmani ◽  
N. Muhammad Aslaam
Keyword(s):  
Supply Chain ◽  
North Dakota ◽  
Programming Model ◽  
Single Mode ◽  
Cost Effective ◽  
Mixed Integer ◽  
Strategic Decisions ◽  
Multimodal Transport ◽  
The Impact

In this study, a mixed integer linear programming model that integrates multimodal transport—truck and rail—into the switchgrass-based bioethanol supply chain was formulated. The objective of this study was to minimize the total cost for cultivation and harvesting, infrastructure, the storage process, bioethanol production, and transportation. Strategic decisions, including the number and location of intermodal facilities and biorefineries, and tactical decisions, such as the amount of biomass shipped, processed, and converted into bioethanol, were validated by using North Dakota as a case study. It was found that the multimodal transport scenario was more cost effective than a single mode of transport (truck) and resulted in a lower cost for bioethanol. A sensitivity analysis was conducted to demonstrate the impact of key factors in the decision to use multimodal transport in a switchgrass-based bioethanol supply chain and on the cost of bioethanol.

scholarly journals A cost-effective decision-making algorithm for an RFID-enabled HMSC network design

2017 ◽  
Vol 117 (9) ◽  
pp. 1782-1799 ◽  
Author(s):  
Ahmed Mohammed ◽  
Qian Wang ◽  
Xiaodong Li
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Food Supply ◽  
Programming Model ◽  
Meat Products ◽  
Cost Effective ◽  
Mixed Integer ◽  
Food Supply Chain ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers. Design/methodology/approach First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them. Findings The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network. Research limitations/implications This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.

scholarly journals Optimal Location of Biogas Plants in Supply Chains under Carbon Effects: Insight from a Case Study on Animal Manure in North Dakota

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yong Shin Park ◽  
Joseph Szmerekovsky ◽  
Alan Dybing
Keyword(s):  
Supply Chain ◽  
Environmental Impact ◽  
Supply Chains ◽  
North Dakota ◽  
Carbon Emissions ◽  
Animal Manure ◽  
Mixed Integer ◽  
Animal Waste ◽  
The Impact

Faced with increasing concerns over the negative environmental impact due to human and industrial activities, biomass industry practitioners and policy makers have great interest in green supply chains to reduce carbon emissions from supply chain activities. There are many studies which model the biomass supply chain and its environmental impact. However, animal waste sourced biogas supply chain has not received much attention in the literature. Biogas from animal manure not only provides energy efficiency, but also minimizes carbon emissions compared to existing biomass products. Therefore, this study proposes a mixed integer linear program that minimizes total supply costs and carbon emissions from an animal waste sourced biogas supply chain while it also incorporates carbon price in the model to see the impact of a carbon policy on tactical and strategic supply chain decisions. To validate the model proposed, a case study of North Dakota is adopted where there is a high potential for a biogas plant to be developed. The results of our optimization experiment indicate that supply chain performance in terms of both costs and emissions is very sensitive to a carbon pricing mechanism.

scholarly journals Impact of government policies on Sustainable Petroleum Supply Chain (SPSC): A case study – Part II (The State of Nebraska)

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Davoud Ghahremanlou ◽  
Wieslaw Kubiak
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Real Life ◽  
The State ◽  
Policy Impact ◽  
Strategic Decisions ◽  
York County ◽  
The Government ◽  
The Impact

The accompanying part I (Ghahremanlou and Kubiak 2020) developed the Lean Model (LM), a two-stage stochastic programming model which incorporates Renewable Fuel Standard 2 (RFS2), Tax Credits, Tariffs, and Blend Wall (BW), to study the policy impact on the Sustainable Petroleum Supply Chain (SPSC) using cellulosic ethanol. The model enables us to study the impact by running computational experiments more efficiently and consequently by arriving at robust managerial insights much faster. In this paper, we present a case study of the policy impact on the SPSC in the State of Nebraska using the model. The case study uses available real-life data. The study shows that increasing RFS2 does not impact the amount of ethanol blended with gasoline but it might lead to bankruptcy of the refineries. We recommend that the government consider increasing the BW because of its positive economic, environmental and social impacts. For the same reason, we recommend that the tax credit for blending the US produced ethanol with gasoline be at least 0:189 $/gal and the tariff for imported ethanol be at least 1:501 $/gal. These also make the State independent from foreign ethanol thereby enhancing its energy security. Finally, the change in policy impacts the SPSC itself, most importantly it influences the strategic decisions, however setting up a bio-refinery at York county and a blending site at Douglas county emerge as the most robust location decisions against the policy change in the study.

scholarly journals Impact of government policies on Sustainable Petroleum Supply Chain (SPSC): A case study – Part I (Models)

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Davoud Ghahremanlou ◽  
Wieslaw Kubiak
Keyword(s):  
Supply Chain ◽  
General Model ◽  
Programming Model ◽  
The United States ◽  
Policy Impact ◽  
Renewable Fuel Standard ◽  
Stochastic Programming Model ◽  
The Government ◽  
The Impact

Environmental concerns and energy security have led governments to establish legislations to convertConventional Petroleum Supply Chain (CPSC) to Sustainable Petroleum Supply Chain (SPSC). The United States(US), one of the biggest oil consumers in the world, has created regulations to manage ethanol production and con-sumption for the last half century. Though these regulations have created new opportunities, they have also added newburdens to the obligated parties. It is thus key for the government, the obligated parties, and related businesses to studythe impact of the policies on the SPSC. We develop a two-stage stochastic programming model, General Model (GM),which incorporates Renewable Fuel Standard 2 (RFS2), Tax Credits, Tariffs, and Blend Wall (BW) to study the policyimpact on the SPSC using cellulosic ethanol. The model, as any other general model available in the literature, makesit highly impractical to study the policy impact due to the model’s computational complexity. We use the GM to derivea Lean Model (LM) to study the impact by running computational experiments more efficiently and consequently byarriving at robust managerial insights much faster. We present a case study of the policy impact on the SPSC in theState of Nebraska using the LM in the accompanying part II (Ghahremanlou and Kubiak 2020).

scholarly journals OPTIMISING THE ANALYSIS STAGE IN THE INTERNATIONALISATION OF MANUFACTURING OPERATIONS

2021 ◽  
Vol 32 (2) ◽  
Author(s):  
Fabio Comer ◽  
Josefa Mula ◽  
Manuel Díaz-Madroñero ◽  
Hanzel Grillo
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Mixed Integer ◽  
Strategic Decisions ◽  
Manufacturing Operations ◽  
Proposed Model ◽  
Production And Distribution ◽  
Global Supplier ◽  
Near Future

The internationalisation of the manufacturing operations process includes decision-making about new facility implementation (NFI) and global supplier network development (GSND), whose first step is to analyse the situation of a company and its environment. The purpose of this paper is to investigate the optimal design of a manufacturing production and distribution network for global small- and medium-sized enterprises (SMEs). This research uses a mixed-integer linear programming (MILP) model to support decision-making in the analysis stage of the internationalisation of manufacturing operations for global SMEs. A real- world case study is presented to illustrate the application of the proposed model. Different scenarios were evaluated not only to identify the strengths and limitations of the mathematical programming model, but to also provide support for the next strategic decisions that the examined company has to make in the near future.

scholarly journals Hybrid model to design a distribution network in contract farming

DYNA ◽  
2019 ◽  
Vol 86 (208) ◽  
pp. 102-109 ◽  
Author(s):  
Rafael Granillo-Macias ◽  
Isidro Jesus Gonzalez Hernandez ◽  
Jose Luis Martinez-Flores ◽  
Santiago Omar Caballero-Morales ◽  
Elias Olivarez-Benitez
Keyword(s):  
Hybrid Model ◽  
Programming Model ◽  
Distribution Network ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Problem ◽  
Contract Farming ◽  
The Impact ◽  
Distribution Cost

This paper suggests a hybrid model to solve a distribution problem incorporating the impact of uncertainty in the solution. The model combines the deterministic approach and the simulation including stochastic variables such as harvest yield, loss risk and penalties/benefits to design a distribution network with the minimal cost. Through a case study that includes farmers, hubs and malt producers in the supplying chain of barley in Mexico, nine possible scenarios were analyzed to plan and distribute the harvested grain based on contract farming. This approach gets an optimal solution through an iterative process simulating the suggested solution by a mixed-integer linear programming model under uncertain conditions. The results show the convenience of maintaining the operation between four and five hubs depending on the possible scenario; besides, the variation of the levels of the barley producers’ capacities are key elements in the planning to minimize the distribution cost throughout the suggested 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.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

scholarly journals Modeling and Optimization Sustainable Forest Supply Chain Considering Discount in Transportation System and Supplier Selection under Uncertainty

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 964
Author(s):  
Komeyl Baghizadeh ◽  
Dominik Zimon ◽  
Luay Jum’a
Keyword(s):  
Supply Chain ◽  
Working Hours ◽  
Mixed Integer ◽  
Forest Industry ◽  
Northern Iran ◽  
Suggested Approach ◽  
Tactical Decisions ◽  
Environmental Goals ◽  
Forest Supply Chain ◽  
The Impact

In recent decades, the forest industry has been growingly expanded due to economic conditions, climate changes, environmental and energy policies, and intense demand changes. Thus, appropriate planning is required to improve this industry. To achieve economic, social and environmental goals, a supply chain network is designed based on a multi-period and multi-product Mixed-Integer Non-Linear Programming (MINLP) model in which the objective is to maximize the profit, minimize detrimental environmental effects, improve social effects, and minimize the number of lost demands. In addition, to improve forest industry planning, strategic and tactical decisions have been implemented throughout the supply chain for all facilities, suppliers and machinery. These decisions significantly help to improve processes and product flows and to meet customers’ needs. In addition, because of the presence of uncertainty in some parameters, the proposed model was formulated and optimized under uncertainty using the hybrid robust possibilistic programming (HRPP-II) approach. The -constraint technique was used to solve the multi-objective model, and the Lagrangian relaxation (LR) method was utilized to solve the model of more complex dimensions. A case study in Northern Iran was conducted to assess the efficiency of the suggested approach. Finally, a sensitivity analysis was performed to determine the impact of important parameters on objective functions. The results of this study show that increasing the working hours of machines instead of increasing their number, increasing the capacity of some facilities instead of establishing new facilities and expanding the transport fleet has a significant impact on achieving predetermined goals.

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