This article addresses the optimal design and planning of cellulosic ethanol supply chains under economic, environmental, and social objectives. The economic objective is measured by the total annualized cost, the environmental objective is measured by the life cycle greenhouse gas emissions, and the social objective is measured by the number of accrued local jobs. A multiobjective mixed-integer linear programming (mo-MILP) model is developed that accounts for major characteristics of cellulosic ethanol supply chains, including supply seasonality and geographical diversity, biomass degradation, feedstock density, diverse conversion pathways and byproducts, infrastructure compatibility, demand distribution, regional economy, and government incentives. Aspen Plus models for biorefineries with different feedstocks and conversion pathways are built to provide detailed techno-economic and emission analysis results for the mo-MILP model, which simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The mo-MILP problem is solved with an e-constraint method; and the resulting Pareto-optimal curves reveal the tradeoff between the economic, environmental, and social dimensions of the sustainable biofuel supply chains. The proposed approach is illustrated through two case studies for the state of Illinois. © 2011 American Institute of Chemical Engineers AIChE J, 2012

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Optimal design of sustainable cellulosic biofuel supply chains: Multiobjective optimization coupled with life cycle assessment and input–output analysis

Biomass-to-bioenergy and biofuel supply chain optimization: Overview, key issues and challenges

Quantitative models for managing supply chain risks: A review

This paper addresses the optimal design and planning of biomass-to-liquids (BTL) supply chains under economic and environmental criteria. The supply chain consists of multisite distributed–centralized processing networks for biomass conversion and liquid transportation fuel production. The economic objective is measured by the total annualized cost, and the measure of environmental performance is the life cycle greenhouse gas emissions. A multiobjective, multiperiod, mixed-integer linear programming model is proposed that takes into account diverse conversion pathways and technologies, feedstock seasonality, geographical diversity, biomass degradation, infrastructure compatibility, demand distribution, and government incentives. The model simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The problem is formulated as a bicriterion optimization model and solved with the ...

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Life Cycle Optimization of Biomass-to-Liquid Supply Chains with Distributed–Centralized Processing Networks

Biofuels are identified as the potential solution for depleting fossil fuel reserves, increasing oil prices, and providing a clean, renewable energy source The major barrier preventing the commercialization of lignocellulosic biorefineries is the complex conversion process and their respective supply chain Efficient supply chain management of a lignocellulosic biomass is crucial for success of second generation biofuels This paper systematically describes energy needs, energy targets, biofuel feedstocks, conversion processes, and finally provides a comprehensive review of Biomass Supply Chain (BSC) design and modeling Specifically, the paper presents a detailed review of mathematical programming models developed for BSC and identifies key challenges and potential future work This review will provide readers with a starting point for understanding biomass feedstocks and biofuel production as well as detailed analysis of the BSC modeling and design

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

This paper presents a general optimization model that enables the selection of fuel conversion technologies, capacities, biomass locations, and the logistics of transportation from the locations of forestry resources to the conversion sites and then to the final markets. A mixed integer linear programming (MILP) model has been formulated and implemented in a commercial software package (GAMS) using databases built in Excel. The MILP represents decisions regarding (1) the optimal number, locations, and sizes of various types of processing plants, (2) the amounts of biomass, intermediate products, and final products to be transported between the selected locations over a selected period, and maximizes the objective function of overall profit. The model has been tested based on an industry-representative data set that contains information on the existing wood resources, final product market locations and demands, and candidate locations and sizes for different types of processing plants, as well as the costs associated with the various processing units and transportation of materials, covering the Southeastern region of the United States. The model is applied to design both a distributed, and a more centralized, conversion system. The overall profits, values, cost, and supply network designs of both systems are analyzed using the optimization model. In particular, we investigate: 1) which parameters have major effect on the overall economics, and 2) the benefits of going to more distributed types of processing networks, in terms of the overall economics and the robustness to demand variations.

Design of biomass processing network for biofuel production using an MILP model

Two stage stochastic bilevel programming model of a pre-established timberlands supply chain with biorefinery investment interests

Analysis and comparison of single period single level and bilevel programming representations of a pre-existing timberlands supply chain with a new biorefinery facility

This work studies the supply allocation problem, using a Stackelberg game, for an established timberlands supply chain with an additional decision of a new biorefinery investment. In a timberlands system, harvester and manufacturer decision makers have separate objectives to maximize their respective profits. This interaction is represented with a turn based Stackelberg game. The harvesters make its decisions first on the quantity harvested, and the manufacturers make their decisions on how much to utilize. This game is represented in a bilevel mathematical programming model. The novel feature of this paper’s bilevel formulation is the inclusion of parametric uncertainty in a two stage model. The first stage problem involves logistical decisions around biorefinery investments, such as location and capacity, while the second stage problem is a bilevel timberlands model with parameter uncertainty. Studying this problem formulation revealed interesting insight concerning solving multiperiod problems with bilevel stages as well as decision maker behavior for the timberlands model.

Two Stage Bilevel Programming Approach for Representation of Biorefinery Investment Decision Making in a Pre-Established Timberlands Supply Chain

In the push for clean and renewable fuels, timber-derived biomass is a promising frontier for biofuel production in the United States. This work models a timberlands supply chain, specifically analyzing long-term land management strategies for harvesters and production capacity decisions for manufacturers. Introduction of a new biorefinery investment means these management strategies must be adapted to continue providing consistent material flows to manufacturers. The established timberlands supply chain was modeled with a cyclic scheduling framework. Studies were performed around the generation of initial states for the system and how harvest consistency constraints could affect them. These initial states were used in simulations with a modified cyclic scheduling framework. An initial start-up period was added to initiate biofuel production and provide time to adapt the timberlands. The duration of the start-up period was varied to determine how duration influenced the adaptation of the timberlands.

Craig Whittaker

Papers

Design of biomass processing network for biofuel production using an MILP model

Two stage stochastic bilevel programming model of a pre-established timberlands supply chain with biorefinery investment interests

Analysis and comparison of single period single level and bilevel programming representations of a pre-existing timberlands supply chain with a new biorefinery facility

Two Stage Bilevel Programming Approach for Representation of Biorefinery Investment Decision Making in a Pre-Established Timberlands Supply Chain

Optimal Harvest Management Adaptation for a New Biorefinery Investment in a Timberlands Supply Chain Using a Modified Cyclic Scheduling Model