Given the increasing demand for energy, climate change, and environmental concern of fossil fuels, it is becoming increasingly significant to find alternative renewable energy sources. Bioethanol as one sort of cellulosic biofuel produced from lignocellulosic biomass feedstocks has shown great potential as a renewable resource. Delivering a competitive, sustainable biofuel product requires comprehensive supply chain planning and design. Developing economically and environmentally optimal supply chain models is necessary in this context. Also, designing biomass bioethanol supply chain (BBSC) models addressing social issues requires using second-generation biomass which is not a source of food for humans. Currently, corn as a first-generation feedstock is the primary source of bioethanol in the United States which has given growth to new social issues such as the food versus fuel debate. Considering incentives for first-generation bioethanol producers to switch to second-generation biomass and associated production technologies will help to address such social issues. The scope of this study focuses on analyzing economic and environmental market incentives for second-generation bioethanol producers while considering different carbon policies as penalties and restrictions for emissions coming from BBSC activities. First, we develop an integrated life cycle emission and energy optimization model for analyzing an entire second-generation bioethanol supply chain using switchgrass as the source of biomass while finding the most appropriate potential locations for building new cellulosic biorefineries in North Dakota. Second, we propose a supply chain model by comparing a first-generation (corn) and a second-generation (corn stover) bioethanol supply chain to analyze how policymakers can incentivize first-generation bioethanol producers to switch their technology and biomass supply from first-generation to second-generation biomass. Third, we develop the model further by investigating the impact of four different carbon policies including the carbon tax, carbon cap, carbon cap-and-trade, and carbon offset on the supply chain strategic and operational decisions. This research will help to design robust BBSCs focused on sustainability in order to optimally utilize second-generation biomass resources in the future. The findings can be utilized by renewable energy policy decision makers, bioethanol producers, and investors to operate in a competitive market while protecting the environment.

Biomass-based CHP (bCHP) can provide reliable electricity in remote and rural areas because it is an on-site generation resource, and it is designed to support continued operations in the event of a disaster. However, the benefits of such facilities can only be realized if a reliable and economical feedstock supply system is designed, given the system not only efficiently transports biomass under normal scenarios (e.g., when depots and transportation links are functioning properly) but also hedges against unexpected infrastructure/transportation link failures due to severe weather events (e.g., hurricanes). To serve this purpose, this study proposes a three-stage stochastic programming model to design a reliable feedstock supply system, where decisions are made sequentially to realistically represent pre-and-post disaster situations) under uncertain infrastructure status (e.g., unavailability of the road and facility conditions) and customer demand situations. In stage one, pre-disaster decisions are made (e.g., the opening of depots and regular feedstock transportation decisions), while stages two and three represent, respectively, immediate decisions following a disaster (e.g., damaged timber transportation, pellet production) and post-disaster decisions (e.g., transportation pellets to end-users, storage) with a timeframe between several days to weeks. By collecting data from 15 coastal rural counties in Mississippi, we create a real-life case study and derive important managerial insights. Our experimental results reveal that the biomass-to-bCHP supply chain decisions (e.g., depot location, storage, transportation decisions) are highly sensitive to intensity and the probabilistic infrastructure availability following a hurricane. The second chapter extends the research by introducing high and low priority end-users so the demand prioritization is met.

As competition for fossil fuels accelerates, alternative sources of chemicals, fuels, and energy production become more appealing to researchers and the layman. Among the candidates to fill this growing niche is lignocellulosic biomass. Many researchers have examined supply chain design and optimization for biofuel and bioenergy production throughout the years. However, these models often fail to capture the variability and uncertainty inherent to the biomass supply chain. Multiple factors with high degrees of stochasticity can have major impacts on the performance of a biorefinery: weather, biomass quality, feedstock availability, and market demand for products are just a few. To begin to address this issue, a discrete event simulation model has been developed to examine the economic performance of a region specific, multifeedstock biorefinery supply chain. Probability distributions developed for product demand and feedstock supply begin to address the random nature of the supply chain. Model development is discussed in the context of a multidisciplinary framework for biorefinery supply chain design. A case study, sensitivity analysis, and scenario analysis, are utilized to examine the capabilities of the model.

This dissertation studies two important problems in the field of biomass supply chain network. In the first part of the dissertation, we study the pre-disaster planning problem that seeks to strengthen the links between the multi-modal facilities of a biomass supply chain network. A mixed-integer nonlinear programming model is developed to determine the optimal locations for multi-modal facilities and bio-refineries, offer suggestions on reliability improvement at vulnerable links, production at bio-refineries, and make transportation decision under both normal and disrupted scenarios. The aim is to assist investors in determining which links’ reliability can be improved under specific budget limitations so that the biouel supply chain network can prevent possible losses when transportation links are disrupted because of natural disasters. We used states Mississippi and Alabama as a testing ground for our model. As part of numerical experimentation, some realistic hurricane scenarios are presented to determine the potential impact that pre-investing may have on improving the bio-mass supply chain network’s reliability on vulnerable transportation links considering limited budget availability. In the second part of the dissertation, we study the impact of feedstock supply uncertainty on the design and management of an inbound biomass coiring supply chain network. A two-stage stochastic mixed integer linear programming model is developed to determine the optimal use of multi-modal facilities, biomass storage and processing plants, and shipment routes for delivering biomass to coal plants under feedstock supply uncertainty while considering congestion into account. To represent a more realistic case, we generated a scenario tree based on the prediction errors obtained from historical and forecasted feedstock supply availability. We linearized the nonlinear problem and solved with high quality and in a time efficient manner by using a hybrid decomposition algorithm that connects a Constraint generation algorithm with Sample average approximation algorithm and enhanced Progressive hedging algorithm. We used states Mississippi and Alabama as a testing ground for our study and conducted thorough computational experiments to test our model and to draw managerial insights.

In this work, we address a variety of problems with applications to `ethanol production from biomass', `agile manufacturing' and `mass customization' domains. Our motivation stems from the potential use of biomass as an alternative to non-renewable fuels, the prevalence of `flexible manufacturing systems', and the popularity of `mass customization' in today's highly competitive markets. Production scheduling and design and optimization of logistics network mark the underlying topics of our work. In particular, we address three problems, Biomass Logistics Problem, Hybrid Flow Shop Scheduling Problem, and Stochastic Demand Assembly Job Scheduling Problem. The Biomass Logistics Problem is a strategic cost analysis for setup and operation of a biomass supply chain network that is aimed at the production of ethanol from switchgrass. We discuss the structural components and operations for such a network. We incorporate real-life GIS data of a geographical region in a model that captures this problem. Consequently, we develop and demonstrate the effectiveness of a `Nested Benders' based algorithm for an efficient solution to this problem. The Hybrid Flow Shop Scheduling Problem concerns with production scheduling of a lot over a two-stage hybrid flow shop configuration of machines, and is often encountered in `flexible manufacturing systems'. We incorporate the use of `lot-streaming' in order to minimize the makespan value. Although a general case of this problem is NP-hard, we develop a pseudo-polynomial time algorithm for a special case of this problem when the sublot sizes are treated to be continuous. The case of discrete sublot sizes is also discussed for which we develop a branch-and-bound-based method and experimentally demonstrate its effectiveness in obtaining a near-optimal solution. The Stochastic Demand Assembly Job Scheduling Problem deals with the scheduling of a set of products in a production setting where manufacturers seek to fulfill multiple objectives such as `economy of scale' together with achieving the flexibility to produce a variety of products for their customers while minimizing delivery lead times. We design a novel methodology that is geared towards these objectives and propose a Lagrangian relaxation-based algorithm for efficient computation. / Doctor of Philosophy / In this work, we organize our research efforts in three broad areas - Biomass Supply Chain, Hybrid Flow Shop, and Assembly Job Shop, which are separate in terms of their application but connected by scheduling and logistics as the underlying functions. For each of them, we formulate the problem statement and identify the challenges and opportunities from the viewpoint of mathematical decision making. We use some of the well known results from the theory of optimization and linear algebra to design effective algorithms in solving these specific problems within a reasonable time limit. Even though the emphasis is on conducting an algorithmic analysis of the proposed solution methods and in solving the problems analytically, we strive to capture all the relevant and practical features of the problems during formulation of each of the problem statement, thereby maintaining their applicability. The Biomass Supply Chain pertains to the production of fuel grade ethanol from naturally occurring biomass in the form of switchgrass. Such a system requires establishment of a supply chain and logistics network that connects the production fields at its source, the intermediate points for temporary storage of the biomass, and bio-energy plant and refinery at its end for conversion of the cellulosic content in the biomass to crude oil and ethanol, respectively. We define the components and operations necessary for functioning of such a supply chain. The Biomass Logistics Problem that we address is a strategic cost analysis for setup and operation of such a biomass supply chain network. We focus our attention to a region in South Central Virginia and use the detailed geographic map data to obtain land use pattern in the region. We conduct survey of existing literature to obtain various transportation related cost factors and costs associated with the use of equipment. Our ultimate aim here is to understand the feasibility of running a biomass supply chain in the region of interest from an economic standpoint. As such, we represent the Biomass Logistics Problem with a cost-based optimization model and solve it in a series of smaller problems. A Hybrid Flow Shop (HFS) is a configuration of machines that is often encountered in the flexible manufacturing systems, wherein a particular station of machines can execute processing of jobs/tasks simultaneously. In our work, we approach a specific type of HFS, with a single machine at the first stage and multiple identical machines at the second stage. A batch or lot of jobs/items is considered for scheduling over such an HFS. Depending upon the area of application, such a batch is either allowed to be split into continuous sections or restricted to be split in discrete sizes only. The objective is to minimize the completion time of the last job on its assigned machine at the second stage. We call this problem, Hybrid Flow Shop Scheduling Problem, which is known to be a hard problem in literature. We aim to derive the results which will reduce the complexity of this problem, and develop both exact as well as heuristic methods in order to obtain near-optimal solution to this problem. An Assembly Job Shop is a variant of the classical Job Shop which considers scheduling a set of assembly operations over a set of assembly machines. Each operation can only be started once all the other operations in its precedence relationship are completed. Assembly Job Shop are at the core of some of the highly competitive manufacturing facilities that are principled on the philosophy of Mass Customization. Assuming an inherent nature of demand uncertainty, this philosophy aims to achieve ‘economy of scale’ together with flexibility to produce a variety of products for the customers while minimizing the delivery lead times simultaneously. We incorporate some of these challenges in a concise framework of production scheduling and call this problem as Stochastic Demand Assembly Job Scheduling Problem. We design a novel methodology that is geared towards achieving the set objectives and propose an effective algorithm for efficient computation.

La sfida nel 21esimo secolo è quella di fornire cibo e energia ad un mondo in continua crescita demografica e allo stesso tempo conservare l’ambiente. In questa tesi uno scenario alternativo di uso del suolo per la produzione di bioenergia è stato testato: le fasce tampone bioenergetiche. Considerate le problematiche ambientali legate al trilemma “cibo-energia-ambiente”, la struttura del Millennium Ecosystem Assessment sui servizi ecosistemici (SE) fornisce l’opportunità di esaminare l’impatto ambientale di questo nuovo scenario bioenergetico. In questa tesi ho mirato a determinare in che misura le colture bioenergetiche poliennali influenzino la fornitura multipla di SE quando coltivate come fasce tampone. Per raggiungere questo obiettivo, ho combinato una revisione sistematica della letteratura sui SE forniti da colture energetiche poliennali (CEP) con una prova sperimentale su fasce tampone bioenergetiche. Applicando una metodologia di attribuzione di punteggi agli impatti sui SE estratti dal materiale bibliografico raccolto, ho mostrato come coltivando le CEP lungo i margini dei campi coltivati esista una grande opportunità per sostenere la fornitura multipla di SE. La coltivazione delle CEP come fasce tampone adiacenti a campi agricoli può migliorare i SE di regolazione del clima, dell’acqua e della biodiversità, sostenere la salute del suolo e fornire biomassa dedicata alla produzione di bioenergia. Al contrario, la conversione di margini di campo di prati stabili ha mostrato un impatto netto negativo sulla fornitura multipla di SE. Tuttavia, due sono i principali svantaggi che sono stati individuati relativamente alla creazione e alla gestione delle fasce tampone bioenergetiche. Primo, diversi sono i fattori sito-specifici di tipo idro-pedologico lungo i margini dei campi che devono essere tenuti in considerazione poiché possono avere un impatto negativo sull’affrancamento delle colture e la loro produttività a medio-lungo termine. Secondo, riguardo la catena di approvvigionamento della biomassa, uno spazio di lavoro limitato per le macchine agricole è stato riconosciuto come principale inconveniente per le fasce tampone bioenergetiche rispetto alle CEP coltivate in pieno campo. Questo limite logistico di natura spaziale può inevitabilmente incrementare i tempi e le operazioni di taglio e raccolta della biomassa e quindi in ultima il consumo di combustili fossili. Grazie ad una prova sperimentale su fasce tampone bioenergetiche condotta in un terreno sabbioso-limoso con falda acquifera poco profonda contaminata da nitrati di origine agricola, si è dimostrato come fasce tampone coltivate con miscanto e salice siano in grado di intercettare e rimuovere i nitrati in falda (>60%) tanto quanto fasce tampone con specie avventizie. CEP come miscanto e salice, grazie ai loro apparati radicali profondi, hanno mostrato essere in grado di promuovere delle relazioni pianta-suolo-microorganismi lungo l’intero profilo del suolo utili ai fini ambientali delle fasce tampone bioenergetiche. Infatti, negli strati più profondi, una maggiore biomassa radicale ha portato le CEP a superare le specie avventizie in termini di rimozione biologica dei nitrati dal suolo e mitigazione potenziale dei gas serra. Inoltre, i risultati relativi alla produzione di biomassa e le asportazioni di N legata alla fase di raccolta hanno confermato ulteriormente come la coltivazione di CEP lungo i corsi d’acqua sia una strategia win-win: produzione di biomassa e protezione dell’ambiente. In conclusione, il potenziale rivelato dalle CEP in termini di fornitura multipla di SE suggerisce che la loro coltivazione, come elementi paesaggistici perenni in posizioni strategiche all'interno di paesaggio agricolo, è un'opzione promettente per promuovere l'intensificazione ecologicamente sostenibile degli agroecosistemi. / The 21st century will challenge agriculture to feed and fuel a growing world while conserving the environment. In this thesis an alternative bioenergy land use scenario to the conversion of marginal land has been tested: the bioenergy buffers. Given the environmental issues related to “food-energy-environment” trilemma, the Millennium Ecosystem Assessment framework on ES provides an opportunity to examine the environmental impacts of this new bioenergy land use scenario. In this thesis I aimed to determine to what extent do the perennial bioenergy crops affect the delivery of multiple ES when cultivated as bioenergy buffers. To reach this aim, I combined a systematic revision of literature on ES provided by perennial bioenergy crops with a field experiment on bioenergy buffers. Applying an impact scoring methodology to the effects on ES extracted from literature, I showed that, cultivating perennial bioenergy crops along field margins of former croplands offer a great opportunity to sustain the provision of multiple ES. The cultivation of perennial bioenergy crops on field margins can improve climate, biodiversity and water regulation services, sustain soil health and provide biomass for energetic purposes. On the contrary, grassland conversion showed a net negative impact on multiple ES provision. Nevertheless, I found two main shortcomings related to bioenergy buffers establishment and management. First, several site-specific factors along field margins must be taken into account, because they can affect crop establishment and buffers long-term productivity. Second, regarding to biomass supply chain, a limited working space for the farm machinery operations has been recognized as the main disadvantages of bioenergy buffers compared to large-scale bioenergy plantations. This spatial logistics constraint may inevitably increase harvest and collection operation times and fossil fuel consumption. Conducting a field experiment with bioenergy buffers in a nitrate-enriched shallow groundwater, I showed that miscanthus and willow buffers are able to efficiently intercept and remove from groundwater the incoming NO3-N as much as buffer strips with spontaneous species. Yet, due to their deep rooting systems, bioenergy buffers promote significant plant-microbial linkages along the soil profile. At deeper soil layers, a higher fine root biomass led perennial bioenergy crops to outperform patches of adventitious vegetation in terms of biological N removal from soil and belowground GHG mitigation potential. The results on biomass production and N removal via harvesting further confirmed that the cultivation of perennial bioenergy crops along watercourses is an effective win-win strategy: biomass production and protection of the environment. In conclusion, the revealed potential of perennial bioenergy crops on multiple ES provision implies that their cultivation as perennial landscape elements in strategic locations within landscape is a promising option to promote the ecological sustainable intensification of agroecosystems.