Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must form an integral part of the design problem. This work proposes an alternative treatment of the imprecision (demands) by using fuzzy concepts. In this study, we introduce a new approach to the design problem based on a multiobjective genetic algorithm, taking into account simultaneously maximization of the net present value NPV ~ and two other performance criteria, i.e. the production delay/advance and a flexibility criterion. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage. Besides, a hybrid selection method Pareto rank-tournament was proposed and showed a better performance than the classical Goldberg’s wheel, systematically leading to a higher number of non-dominated solutions

Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

This paper addresses the problem of the optimal design of batch plants with imprecise demands in product amounts. The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must constitute a basic part of the design problem. Rather than resorting to a traditional probabilistic approach for modeling the imprecision on product demands, this work proposes an alternative treatment by using fuzzy concepts. The design problem is tackled by introducing a new approach based on a multiobjective genetic algorithm, combined wit the fuzzy set theory for computing the objectives as fuzzy quantities. The problem takes into account simultaneous maximization of the fuzzy net present value and of two other performance criteria, i.e. the production delay/advance and a flexibility index. The delay/advance objective is computed by comparing the fuzzy production time for the products to a given fuzzy time horizon, and the flexibility index represents the additional fuzzy production that the plant would be able to produce. The multiobjective optimization provides the Pareto's front which is a set of scenarios that are helpful for guiding the decision's maker in its final choices. About the solution procedure, a genetic algorithm was implemented since it is particularly well-suited to take into account the arithmetic of fuzzy numbers. Furthermore because a genetic algorithm is working on populations of potential solutions, this type of procedure is well adapted for multiobjective optimization

A fuzzy multiobjective algorithm for multiproduct batch plant: Application to protein production

This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the imprecision by using fuzzy concepts. For this purpose, we extended a multiobjective genetic algorithm (MOGA) developed in previousworks, taking into account simultaneously maximization of the net present value (NPV) and two other performance criteria, i.e. the production delay/advance and a flexibility criterion. The former is computed by comparing the fuzzy computed production time to a given fuzzy production time horizon and the latter is based on the additional fuzzy demand that the plant is able to produce. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage

Multiobjective Multiproduct Batch Plant Design Under Uncertainty

This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the imprecision by using fuzzy concepts. For this purpose, we extended a multiobjective genetic algorithm developed in previous works, taking into account simultaneously maximization of the net present value (NPV) and two other performance criteria, i.e. the production delay/advance and a flexibility criterion. The former is computed by comparing the fuzzy computed production time to a given fuzzy production time horizon and the latter is based on the additional fuzzy demand that the plant is able to produce. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage

Knockdown of Myosin Va Isoforms by RNAi as a Tool to Block Melanosome Transport in Primary Human Melanocytes

The movement of melanosomes, dense melanin-containing organelles, within human melanocytes is actin-dependent and mediated through the formation of a Rab27a-Slac2-a–myosin Va (MyoVa) protein complex. We previously showed that only the melanocyte-specific exon F isoforms of MyoVa are involved in melanosome transport to the dendrite extremities. Here, we investigate siRNA to downregulate the exon F-containing isoforms of MyoVa in primary human melanocytes. Efficient and specific knockdown of the MyoVa exon F isofoms were shown at both mRNA and protein levels. Further, a stable shRNA against the MyoVa exon F isoforms was prepared by using a lentiviral system to improve and confirm the silencing effect in hard-to-transfect melanocyte cells. Immunofluorescence microscopy shows that knockdown of the exon F isoforms results in blockade of intramelanocytic melanosome transport due to the inability to form the Rab27a-Slac2-a–MyoVa tripartite complex. Interestingly, the observed phenotypic effect (that is, perinuclear accumulation of melanosomes) is the same as that seen in melanocytes from patients with human Griscelli syndrome causing abnormal pigmentation. We conclude that our siRNA-based strategy provides a previously unreported tool to block the intracellular melanosome movement in primary human melanocytes and may become an innovative drug to treat hyperpigmentation

Uncertainty evaluation of Climatol’s adjustment algorithm applied to daily air temperature time series

The present study investigated the uncertainty associated with Climatol’s adjustment algorithm applied to daily minimum and maximum air temperature. The uncertainty quantification was performed based on several numerical experiments and the benchmark data, that were created in the frame of the INDECIS project. Using a complex approach, the uncertainty was evaluated on different levels of detail (day-to-day evaluation through formalism of random functions and through six statistical metrics) and time resolution (daily and yearly). However, only the main source of potential residual errors was considered, namely station signals introduced into a raw data set to be homogenized/adjusted. Other influencing factors were removed from the analysis or kept almost unchanged. According to our calculations, the Climatol’s adjustment uncertainty, evaluated on the daily scale, varies in time. The width of the residual errors distribution in summer months is substantially less compared to wintertime. The slight seasonality is also observed in the means of the residual errors. The uncertainty evaluation based on the statistical metrics usually neglect such nonstationarity of the residual errors providing just averaged in time assessments. On the other hand, metrics provide detailed information regarding both types of the residual errors, systematic and scatter. The metrics values showed good capability of the Climatol software to remove the systematic errors related to jumps in the means, while the scatter errors are removed from the raw time series with less efficiency. On yearly scale, the uncertainty evaluation was performed for yearly temperature data and several climate extreme indices. The both types of the errors are removed well in yearly time series of the air temperature and the extreme indices. The metrics values also showed significant reduction of the adjustment uncertainty of Climatol’s adjustment. Substantial decreasing of linear trend errors in yearly time series can also be reported.The work was performed in the frame of the INDECIS project, that is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). The work has been partially supported by the Ministry of Education and Science of Kazakhstan (Grant BR05236454) and Nazarbayev University (Grant 090118FD5345)

Un modelo docente para sensibilizar sobre la sostenibilidad empleando la geoinformación

The increase in geoinformation and its integrated use in cloud-based geographic information systems, or Web GIS, facilitates visualization of data and helps to improve our understanding of socio-economic factors as well as the natural landscape. Effective application of these tools in the classroom requires a change in teachers’ pedagogies. Thus, a review of existing pedagogies and a brief questionnaire given to teachers with lots of experience of using Web GIS, was carried out in order to identify how they were integrating online interactive maps into their teaching to make learning more effective. The results led to the development of a series of learning scenarios, or vignettes. These all use the visualization provided by online maps, to encourage more critical and reasoned learning. They also contribute to educating for sustainability, as they highlight trends and interrelationships that are intended to promote transformative action, beyond the theoretical knowledge and application of the Sustainable Development Goals. Direct observation in teacher training classrooms and detailed discussion over each result obtained has validated a teaching model. To support the use of these materials and the application of the model, a training course has been designed for teachers who are new to the profession or those who are interested in integrating these tools into their teaching. To date, trainee teachers who have been introduced to the model have expressed their satisfaction with this new way of working in secondary classrooms.El incremento de la geoinformación y su integración en los sistemas de información geográfica en la nube o SIG Web, facilitan la visualización de los datos y una mejora de la comprensión de la realidad socioeconómica y territorial del paisaje. La efectividad de estas herramientas en las aulas hace necesario un cambio en las pedagogías de los docentes. Así, se ha realizado un seguimiento de las pedagogías existentes y un pequeño cuestionario a profesores experimentados en el empleo de SIG Web con la finalidad de formular cómo integrar los mapas interactivos en línea en la docencia para un aprendizaje más eficiente y elaborar con estos resultados una serie de situaciones de aprendizaje o vignettes. En todas ellas se emplean mapas en línea cuya visualización fomenta el aprendizaje crítico y razonado. Con ellos también se colabora en educar para la sostenibilidad, ya que evidencian tendencias e interrelaciones que se pretende promuevan una acción transformadora, más allá del conocimiento y aplicación teórica de los Objetivos de Desarrollo Sostenible. La observación directa en las aulas de formación del profesorado y una detallada discusión sobre cada resultado que se va obteniendo han validado el modelo docente creado. Para apoyar el empleo de estos materiales y la aplicación del modelo se ha diseñado un curso de formación para el profesorado que se inicia en la profesión o aquél otro con interés en integrar estas herramientas en su docencia. Hasta el momento los profesores en formación que han conocido este modelo han mostrado su satisfacción, su satisfacción por esta nueva forma de trabajar en las aulas de secundaria

Challenges for biodiversity research in Europe.

In 2010, the international year of biodiversity, new policies for preserving biodiversity in Europe and worldwide will be developed as targets set by older policies, such as to halt biodiversity loss in the EU by 2010, were not met. This paper aims at sharing the expertise LERU's members harbour to set the right priorities for new biodiversity policies