This paper addresses an integrated biorefinery supply chain analysis in order to identify the critical factors that can contribute to such system effective modeling. Accordingly, a general mixed integer linear programming (MILP) formulation is developed to support the design of an integrated biorefinery supply chain. The model aims to attain the optimal supply chain configurations from many possible alternatives depending on (i) a large portfolio of biomass sources with distinct physical and chemical characteristics and with different possible locations for its supply; (ii) diverse storage types, with or without pre-processing technologies, and locations; (iv) different transportation modes for every material flows; (iv) different processing technologies to attain a large portfolio of biobased products as well as capacities and locations and (v) manage a large portfolio of end products to be sent to different markets. The model is supported by a database built in Excel in order to allow the application of the model to specific situations and be applied as a decision support system.
The present text surveys and reevaluates the meaning and scope of Ortega y Gasset’s philosophy. The chapters reveal the most important aspects of his history such as the Neokantian training he went thru in Germany as well as his discovery of Husserl’s phenomenology around 1912. The work also covers his original contributions to philosophy namely vital and historical reason - and the cultural and educational mission he proposed to achieve. The Spanish – and to a certain extent the European – circumstance was the milieu from which his work emerged but this does not limit Ortega’s scope. Rather, he believed that universal truths can only emerge from the particulars in which they are embedded. The publication in 2010 of a critical edition of his Complete Works opened worldwide access for many unpublished manuscripts, and some of his lectures. There is renewed interest among students and researchers in Ortega and this book uniquely delivers scholarship on his content in English.
In this paper, we develop a multi-objective model for the design and planning of closed-loop supply chains under demand uncertainty that maximizes the expected net present value (ENPV) and minimizes risk. Four different risk measures are implemented and compared: variance, variability index, downside risk and conditional value-at-risk (CVaR) so as to conclude on these measures adequacy. The model is applied to a European supply chain and the optimal solutions are drawn in a Pareto curve obtained through the ε-constraint method.
This paper presents a novel approach to aid the operational decision-making of scheduling activities in a real-world pipeline used to transport heavy oil derivatives. Heavy oil derivatives are products of less aggregate value, such as fuel oils, e.g. Marine Fuel. These products present some special characteristics for their transport. Indeed due to their viscosity at the room temperature it is impossible to transport them without heating. Thus, when transporting such products through pipelines the entire pipeline network (and the storage tanks) must be maintained heated during the entire pumping process. Such characteristics imply that a specific model oriented to this type of problem must be developed. Some papers have already addressed scheduling decisions within pipeline networks, but the considered scenario is particularly complex. In a heavy oil derivatives pipeline system, it's common to use the same tank for different products during the scheduling horizon, thus changing the aggregate capacity of storage for some products. This procedure is known as the exchange of service of the tank. In order to perform the programmed movements, it's frequent the relocation of a tank from one product to another, decreasing the storage capacity of the former while increasing the later. In addition, a lot of constraints are modelled, as instance, product blending in line, tankage constraints, volume of pipes, production/consumption constraints, and a series of operational requirements. The approach proposed in this work is formed by a decomposition procedure that uses a sequence of mathematic models and heuristicsto solve the problem. The proposed approach is tested using a real-world scenario, composed of a pipeline tree system. The model has been extensively tested in typical operational scenarios. Such models have been solved to optimality in few CPU seconds using a commercial package.
In 2020, the project ‘Stepping Up to Global Challenges (SGC): Empowering Students across the World’ was launched, during the difficult period when the COVID-19 pandemic was spreading across the globe and causing the lockdown of several activities. Education was also severely affected, but, even if the response widely varied at the time, remote learning, telecollaboration and project-based approaches were adopted by many teachers, “encourag[ing] learners to take an active role in their own learning process and to learn how to collaborate successfully with others in order to solve real world challenges” (Mont & Masats, 2018, p. 93). At the Polytechnic of Viseu (Portugal), Ege University (Turkey) and UTH University (Poland), four teachers of English decided to embrace the idea of diluting frontiers and exploring the potential of Information and Communication Technologies through telecollaboration, in which the students developed tasks around the topic of entrepreneurship. Stepping Up to Global Challenges (SGC2): Learning English while Fighting the Outbreak of Covid-19 is a funded project that started in March 2021 and ends in March 2022. Funding for the project was obtained via Apoios Especiais do PV, Tipologia: Projetos que se destinem a implementar metodologias de aprendizagem ativa. For further information, cf. http://politecnicodeviseu.info/apoios-especiais/steppingup-to-global-challenges-2/ The SGC2 team is not responsible for the posters, videos, abstracts and papers compiled in this eBook. The author contributors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
The present text surveys and reevaluates the meaning and scope of Ortega y Gasset’s philosophy. The chapters reveal the most important aspects of his history such as the Neokantian training he went thru in Germany as well as his discovery of Husserl’s phenomenology around 1912. The work also covers his original contributions to philosophy namely vital and historical reason - and the cultural and educational mission he proposed to achieve. The Spanish – and to a certain extent the European – circumstance was the milieu from which his work emerged but this does not limit Ortega’s scope. Rather, he believed that universal truths can only emerge from the particulars in which they are embedded. The publication in 2010 of a critical edition of his Complete Works opened worldwide access for many unpublished manuscripts, and some of his lectures. There is renewed interest among students and researchers in Ortega and this book uniquely delivers scholarship on his content in English.
This paper presents a novel approach to aid the operational decision-making of scheduling activities in a real-world pipeline used to transport heavy oil derivatives. Heavy oil derivatives are products of less aggregate value, such as fuel oils, e.g. Marine Fuel. These products present some special characteristics for their transport. Indeed due to their viscosity at the room temperature it is impossible to transport them without heating. Thus, when transporting such products through pipelines the entire pipeline network (and the storage tanks) must be maintained heated during the entire pumping process. Such characteristics imply that a specific model oriented to this type of problem must be developed. Some papers have already addressed scheduling decisions within pipeline networks, but the considered scenario is particularly complex. In a heavy oil derivatives pipeline system, it's common to use the same tank for different products during the scheduling horizon, thus changing the aggregate capacity of storage for some products. This procedure is known as the exchange of service of the tank. In order to perform the programmed movements, it's frequent the relocation of a tank from one product to another, decreasing the storage capacity of the former while increasing the later. In addition, a lot of constraints are modelled, as instance, product blending in line, tankage constraints, volume of pipes, production/consumption constraints, and a series of operational requirements. The approach proposed in this work is formed by a decomposition procedure that uses a sequence of mathematic models and heuristicsto solve the problem. The proposed approach is tested using a real-world scenario, composed of a pipeline tree system. The model has been extensively tested in typical operational scenarios. Such models have been solved to optimality in few CPU seconds using a commercial package.
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