A multi-objective, hub-and-spoke model to design and manage biofuel supply chains

In this paper we propose a multi-objective, mixed integer linear programming model to design and manage the supply chain for biofuels. This model captures the trade-offs that exist between costs, environmental and social impacts of delivering biofuels. The in-bound supply chain for biofuel plants relies on a hub-and-spoke structure which optimizes transportation costs of biomass. The model proposed optimizes the CO2 style= position: relative; tabindex= 0 id= MathJax-Element-1-Frame \u3eCO2 emissions due to transportation-related activities in the supply chain. The model also optimizes the social impact of biofuels. The social impacts are evaluated by the number of jobs created. The multi-objective optimization model is solved using an augmented ϵ style= position: relative; tabindex= 0 id= MathJax-Element-2-Frame \u3eϵ-constraint method. The method provides a set of Pareto optimal solutions. We develop a case study using data from the Midwest region of the USA. The numerical analyses estimates the quantity and cost of cellulosic ethanol delivered under different scenarios generated. The insights we provide will help policy makers design policies which encourage and support renewable energy production

Stability in shortest path problems

We study three remarkable cost sharing rules in the context of shortest path problems, where agents have demands that can only be supplied by a source in a network. The demander rule requires each demander to pay the cost of their cheapest connection to the source. The supplier rule charges to each demander the cost of the second-cheapest connection and splits the excess payment equally between her access suppliers. The alexia rule averages out the lexicographic allocations, each of which allows suppliers to extract rent in some pre-specified order. We show that all three rules are anonymous and demand-additive core selections. Moreover, with three or more agents, the demander rule is characterized by core selection and a specific version of cost additivity. Finally, convex combinations of the demander rule and the supplier rule are axiomatized using core selection, a second version of cost additivity and two additional axioms that ensure the fair compensation of intermediaries

Stable and weakly additive cost sharing in shortest path problems

In a shortest path problem, agents seek to ship their respective demands; and the cost on a given arc is linear in the flow. Previous works have proposed cost allocations falling in the core of the associated cooperative game. The present work combines core selection with weak versions of the additivity axiom, which allows to characterize a new family of rules. The demander rule charges each demander the cost of their shortest path, and the supplier rule charges the cost of the second-cheapest path while splitting the excess payment equally between access suppliers. With three or more agents, the demander rule is characterized by core selection and a specific version of cost additivity. Convex combinations of the demander rule and the supplier rule are axiomatized using core selection, a second version of cost additivity, and two additional axioms that ensure the fair compensation of intermediaries. With three or more agents, the demander rule is characterized by core selection and a specific version of cost additivity. Finally, convex combinations of the demander rule and the supplier rule are axiomatized using core selection, a second version of cost additivity, and two additional fairness properties.Agencia Estatal de Investigación | Ref. TED2021-130241A-I00Agencia Estatal de Investigación | Ref. PID2020-113440GB-I00Xunta de Galicia | Ref. GPC-ED431B 2022/0

Stability in shortest path problems

We study three remarkable cost sharing rules in the context of shortest path problems, where agents have demands that can only be supplied by a source in a network. The demander rule requires each demander to pay the cost of their cheapest connection to the source. The supplier rule charges to each demander the cost of the second-cheapest connection and splits the excess payment equally between her access suppliers. The alexia rule averages out the lexicographic allocations, each of which allows suppliers to extract rent in some pre-specified order. We show that all three rules are anonymous and demand-additive core selections. Moreover, with three or more agents, the demander rule is characterized by core selection and a specific version of cost additivity. Finally, convex combinations of the demander rule and the supplier rule are axiomatized using core selection, a second version of cost additivity and two additional axioms that ensure the fair compensation of intermediaries

Cost optimization of biofuel production – The impact of scale, integration, transport and supply chain configurations

This study uses a geographically-explicit cost optimization model to analyze the impact of and interrelation between four cost reduction strategies for biofuel production: economies of scale, intermodal transport, integration with existing industries, and distributed supply chain configurations (i.e. supply chains with an intermediate pre-treatment step to reduce biomass transport cost). The model assessed biofuel production levels ranging from 1 to 150 PJ a−1 in the context of the existing Swedish forest industry. Biofuel was produced from forestry biomass using hydrothermal liquefaction and hydroprocessing. Simultaneous implementation of all cost reduction strategies yielded minimum biofuel production costs of 18.1–18.2 € GJ−1 at biofuel production levels between 10 and 75 PJ a−1. Limiting the economies of scale was shown to cause the largest cost increase (+0–12%, increasing with biofuel production level), followed by disabling integration benefits (+1–10%, decreasing with biofuel production level) and allowing unimodal truck transport only (+0–6%, increasing with biofuel production level). Distributed supply chain configurations were introduced once biomass supply became increasingly dispersed, but did not provide a significant cost benefit (<1%). Disabling the benefits of integration favors large-scale centralized production, while intermodal transport networks positively affect the benefits of economies of scale. As biofuel production costs still exceeds the price of fossil transport fuels in Sweden after implementation of all cost reduction strategies, policy support and stimulation of further technological learning remains essential to achieve cost parity with fossil fuels for this feedstock/technology combination in this spatiotemporal context

One-way and two-way cost allocation in hub network problems

We study hub problems where a set of nodes send and receive data from each other. In order to reduce costs, the nodes use a network with a given set of hubs. We address the cost sharing aspect by assuming that nodes are only interested in either sending or receiving data, but not both (one-way flow) or that nodes are interested in both sending and receiving data (two-way flow). In both cases, we study the non-emptiness of the core and the Shapley value of the corresponding cost game

Integrating bio-hubs in biomass supply chains: Insights from a systematic literature review

Biomass sources are geographically scattered, and seasonal changes influence their availability. Variations in location, type, and feedstock quality impose logistical and storage challenges. Such a dispersion and variety of biomass sources, as well as the dispersion of demand points, may undermine the economies of scale and increase the risk of supply shortage. By consolidating biomass preprocessing and distribution activities in bio-hub facilities, they can contribute to the overall resilience of biomass supply chains (BSCs) and ensure a more sustainable and cost-efficient approach to bioenergy production. As such, investigating the advantages and challenges associated with bio-hub implementation can offer invaluable insights on the efficiency and sustainability of BSCs. Despite its critical role, a major part of the literature on BSCs is confined to the decision-making processes related to biomass suppliers and bioconversion facilities. To bridge this research gap, the current study conducts a systematic literature review on bio-hub implementation within BSCs in the period of the last ten years. Shortlisted papers are classified and analyzed meticulously to extract possible improvements from BSC and modeling perspectives. From the BSC viewpoint, one notable gap is the little attention to mid-term and short-term decisions of bio-hub operations such as inventory control, resource management and production planning. Furthermore, the results revealed that environmental and social aspects of bio-hub implementation require considerable attention. From the modeling perspective, findings illustrate the underutilization of integrated approaches to incorporate micro-level and macro-level information in decision-making. In this regard, a number of areas are suggested for further exploration

Strategic design of environmentally and socially sustainable supply networks

The five published articles of this cumulative dissertation deal with the design of supply networks on a strategic level and with a special focus on the operationalization of environmental and social indicators − addressing 16 of the 17 Sustainable Development Goals (SDGs). Based on, inter alia, case studies on Waste Electric and Electronic Equipment (WEEE) as well as lignocellulosic, second-generation bioethanol production in the EU, this work provides best-practice approaches on how to integrate results from applied Industrial Ecology methods (LCA, S-LCA) into Operations Research models (here: multi-objective mixed-integer linear programming). Beside methodological contributions, the dissertation provides insights for policy-makers, practitioners, and academia in terms of environmental, social, and economic benefits and risks of WEEE recovery and second-generation bioethanol production in the EU

On the design of a European bioeconomy that optimally contributes to sustainable development

The inevitability for a change in humankind's resource and fossil energy consumption is demonstrated by global crises such as the climate change, disturbances of natural cycles, and the loss of biodiversity. The sun provides sufficient energy to generate electricity and by photosynthesis, solar radiation is converted into energy chemically bound in biomolecules, which provide building blocks for the production of various materials, chemicals, or fuels. The bioeconomy puts biomass at the center of an economy that attempts to cover resource and energy demand by renewable materials to address the global challenges. However, the finiteness of the terrestrial surface limits renewables, requiring a prioritization of use. The Sustainable Development Goals (SDGs) provide a common ground for global peace, prosperity, improved health and education, reduced inequality, and spur economic growth while tackling climate change and biodiversity loss, making it the most comprehensive framework for defining objectives in the design of the bioeconomy. Against this background, this dissertation is particularly dedicated to the design of bioeconomic value chains based on agroforestry residues in the European Union, considering economic, environmental, and social objectives to optimally exploit the potential to contribute to a sustainable development. All objectives are matched to SDGs to unveil congruencies, conflicts and trade-offs between different goals, and to provide aggregated insights and courses of action in the agroforestry residue-based bioeconomy to politics, the scientific community, and corporate decision-makers. The availability of agroforestry residue volumes and their current uses is the first major concern of a bioeconomy aligned with the SDGs to be assessed in this work. Key findings are that the most promising agricultural residue in the EU is wheat straw, followed by maize stover, barley straw, and rapeseed straw, which together account for about 80% of EU’s cereals and oil crops residues. In forestry, waste bark from the two coniferous species, spruce and pine, are most promising with the highest supplies in Scandinavia and central EU. The time-series-based forecast model predicts a total increase of the bioeconomic potential of the prioritized agricultural feedstocks from 113 Mt in 2017 to 127 Mt in 2030. The forecast indicates the largest increase of all investigated crops for corn stover at up to 20% until 2030, while rapeseed straw production is forecasted to decrease in many regions. To take environmental and social aspects into account on a regional level, along with international competitiveness, this dissertation develops a multi-criteria strategic network design model for the planning of bioeconomic value chains. The environmental and social objectives are derived by means of Life Cycle Assessment and Social Life Cycle Assessment, respectively. The developed set of 35 economic, environmental, and social objective functions allows for the consideration of 16 of the 17 SDGs. The model is applied for the planning of a second-generation bioethanol production network based on agricultural residues in the EU. Single-criteria optimization shows that sustainably available agroforestry residues could substitute up to 22% of the petrol demand in the EU in 2018 under optimal production networks for certain objectives (i.a., global warming). For environmental objectives, the decision to substitute petrol or edible crops-based ethanol has the highest impact. The greenhouse gas benefits could amount to up to 59 Mt CO2 eq., conforming to about 1.35% of the EU’s 2018 total emissions. However, global warming optimization leads to opportunity costs for other objectives. While for ecosystem quality, for example, the achieved value reaches 50% of its optimum, other categories like land use and water consumption could even be net deteriorated by optimizing global warming. For objectives such as land use, only 19% of the total agroforestry residues is used to substitute 100% of the edible crops-based ethanol, which would free up 11.7 billion m2 crop land. Social objectives lead to large and labor-intensive production networks distributed all over the EU. Depending on the social objective, the value creation slightly shifts regionally. To optimize local employment, the network relocates to regions with high unemployment rates, such as Spain, Italy, and parts of France. Economically strong metropolitan regions are at a disadvantage in favor of weaker regions of Central and Eastern EU when optimizing economic development. At best, up to 140,000 new jobs could be created in the EU while 12,000 jobs could be lost due to substitution of reference products. In terms of network extend, most socially and environmentally optimal production networks are similar, although the substitution decision has little impact for social objectives. This means that interesting trade-offs between social and environmental objectives can be found with only minor sacrifices. Economically optimal networks are much smaller and more centralized than environmental ones, and lead to costs of about 0.75 €/l second-generation ethanol. Environmental optimization results in cost between 0.88 €/l to 2.00 €/l, which implies that large-scale bioethanol production is not economically feasible with today’s oil prices and taxes. While the single-criteria optimization reveals conflicts within and between the environment, social, and economic dimensions, Pareto optimization is conducted to unveil trade-offs between conflicting goals. Significant environmental and social benefits can often be realized with only small economic detriments, and vice versa, economic profitability can substantially be improved at low environmental opportunity cost. Furthermore, the applied Pareto optimization shows that the endpoints human health and ecosystem quality are suitable aggregators of environmental impact categories, wherefore they could serve as representative of the environmental dimension in decision-making. Nonetheless, a transparent consideration of a broad range of impacts and knowledge about the categories’ contributions remains indispensable to reveal possible negative consequences of a decision. In a final step, the objective functions are matched to SDGs, and opportunity cost between the objective functions are calculated to unveil congruencies and conflicts between different goals. The assessment of relationships between the different SDGs supports the perception that different aspects of sustainability are not equally directed. Sustainability, expressed by the SDGs, is rather case-specific and varies between a multitude of interdependent social, environmental, and economic criteria. Decision-makers, whether at the corporate level pursuing one or more business objectives or at the policy level, using the SDGs as a framework, should be aware of the reciprocities between the different criteria. The dissertation shows that the European bioeconomy has a great potential to contribute to sustainable development. Multi-criteria optimization models enable sound trade-off decisions that are aligned to the SDGs