Search Results (8)

Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders. Full article

Logistics is becoming more cost competitive while customers and regulatory bodies pressure businesses to disclose their carbon footprints, creating interest in alternative fuels as a decarbonization strategy. This paper provides a thematic review of the role of alternative fuels in sustainable air, land, and sea logistics, their challenges, and potential mitigations. Through an extensive literature survey, we determined that biofuels, synthetic kerosene, natural gas, ammonia, alcohols, hydrogen, and electricity are the primary alternative fuels of interest in terms of environmental sustainability and techno-economic feasibility. In air logistics, synthetic kerosene from hydrogenated esters and fatty acids is the most promising route due to its high technical maturity, although it is limited by biomass sourcing. Electrical vehicles are favorable in road logistics due to cheaper green power and efficient vehicle designs, although they are constrained by recharging infrastructure deployment. In sea logistics, liquified natural gas is advantageous owing to its supply chain maturity, but it is limited by methane slip control and storage requirements. Overall, our examination indicates that alternative fuels will play a pivotal role in the logistics networks of the future. Full article

In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO₂ emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO₂ emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model. Full article

Increasing energy demand and the detrimental environmental impacts of fossil fuels have led to the development of renewable energy sources. Rapid demand growth for wood pellets over the last decade has established wood pellets as a potential renewable energy source in a globally competitive energy market. Integrated decision making including all stakeholders in the wood pellet supply chain (WPSC) is essential for a smooth transition to commercially viable wood pellet production. In this aspect, this study aims to suggest a decision support system for optimizing biomass-based wood pellet production supply chain network design (WPP-SCND). The WPP-SCND decision system minimizes the total supply chain (SC) cost of the system while also reducing carbon emissions associated with wood pellet SC activities. All objective parameters, including biomass availability at the supply terminals, market demand, and biomass production, are considered fuzzy to account for epistemic uncertainty. A fuzzy flexible robust possibilistic programming (fuzzy-FRPP) technique is developed for solving the suggested uncertain WPP-SCND model. The case findings show that the imprecise nature of the parameters has a significant impact on the strategic and tactical decisions in the wood pellet SC. By investing almost 10% of the total cost, robust decisions within the wood pellet SC can be obtained. It is established that the fuzzy-FRPP technique successfully provides robust decisions and achieves a balance between transportation costs, emissions costs, and economies of scale when making capacity decisions. Although the suggested decision support system is used to manage the production and distribution of wood pellets, the insights and solution methodology may be extended to the production of other biofuels. The proposed research may be valuable to authorities involved in planning large-scale wood pellet-related production-distribution projects. Full article

When designing biomass-to-biofuel supply chains, the biomass uncertainty, seasonality and geographical dispersion that affect economic viability need to be considered. This work presents a novel methodology that can optimize the design of biofuel supply chains by adopting a decentralized network structure consisting of a mix of fixed and mobile processing facilities. The model considers a variable biomass yield profile and the mobile fast pyrolysis technology. The mixed-integer linear programming model developed identifies the optimal biofuel production and biomass harvesting schedule schemes under the objective of profit maximization. It was applied in the case study of marginal lands in Scotland, which are assumed to be planted with Miscanthus. The trade-offs observed between economies of scale against the transportation costs, the effect of the relocation costs and the contribution of storage capacity were investigated. The results showed that, in most cases, harvesting is most concentrated during the month of the highest biomass yield, provided that storage facilities are available. Storage capacity plays an important role to widen the operational time window of processing facilities since scenarios with restricted or costly storage resulted in facilities of higher capacity operating within a narrower time window, leading to higher investment costs. Relocation costs proved to have a minor share in the total transportation costs. Full article

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system while site-dependent facility failure and congestion are taken into consideration. The proposed model locates the multi-modal facilities and biorefineries and determines the optimal production, storage, and routing plans in such a way that the overall system cost is minimized. We propose a hybrid Constraint generation-based Rolling horizon algorithm to solve this challenging $\mathcal{NP}$-hard problem. The performance of this algorithm is tested in a example case study with numerical analysis showing that the hybrid algorithm can find near-optimal solutions to large-scale problem instances in a reasonable amount of time. Results indicate that the effect of congestion reduces the usage of multi-modal facilities in the biofuel supply chain network while bio-refineries and multi-modal facilities tend to move away from coastal areas when disruption probabilities are taken into consideration. Full article

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meet conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions. Full article

Logging residues, which refer to the unused portions of trees cut during logging, are important sources of biomass for the emerging biofuel industry and are critical feedstocks for the first-type biofuel facilities (e.g., corn-ethanol facilities). Logging residues are under-utilized sources of biomass for energetic purposes. To support the scaling-up of the bioenergy industry, it is essential to design cost-effective biofuel supply chains that not only minimize costs, but also consider the biomass quality characteristics. The biomass quality is heavily dependent upon the moisture and the ash contents. Ignoring the biomass quality characteristics and its intrinsic costs may yield substantial economic losses that will only be discovered after operations at a biorefinery have begun. This paper proposes a novel bioenergy supply chain network design model that minimizes operational costs and includes the biomass quality-related costs. The proposed model is unique in the sense that it supports decisions where quality is not unrealistically assumed to be perfect. The effectiveness of the proposed methodology is proven by assessing a case study in the state of Tennessee, USA. The results demonstrate that the ash and moisture contents of logging residues affect the performance of the supply chain (in monetary terms). Higher-than-target moisture and ash contents incur in additional quality-related costs. The quality-related costs in the optimal solution (with final ash content of 1% and final moisture of 50%) account for 27% of overall supply chain cost. Based on the numeral experimentation, the total supply chain cost increased 7%, on average, for each additional percent in the final ash content. Full article