Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

INVENTORY CONTROL SYSTEM : Optimization of production system and reliability

The main idea of this research to solve the problem of inventory management for the paper industry SPM PVT limited. The aim of this research was to find a methodology by which the inventory of raw material could be kept at minimum level by means of buffer stock level.The main objective then lies in finding the minimum level of buffer stock according to daily consumption of raw material, finding the Economic Order Quantity (EOQ) reorders point and how much order will be placed in a year to control the shortage of raw material.In this project, we discuss continuous review model (Deterministic EOQ models) that includes the probabilistic demand directly in the formulation. According to the formula, we see the reorder point and the order up to model. The problem was tackled mathematically as well as simulation modeling was used where mathematically tractable solution was not possible.The simulation modeling was done by Awesim software for developing the simulation network. This simulation network has the ability to predict the buffer stock level based on variable consumption of raw material and lead-time. The data collection for this simulation network is taken from the industrial engineering personnel and the departmental studies of the concerned factory. At the end, we find the optimum level of order quantity, reorder point and order days.

Accelerated aging of thick glass second surface silvered reflectors under sandstorm conditions

Concentrated solar power systems are expected to be sited in desert locations where the direct normal irradiation is above 1800 kWh/m2.year. These systems include large solar collector assemblies, which account for a significant share of the investment cost. Solarreflectors are the main components of these solar collector assemblies and dust/sand storms may affect their reflectance properties, either by soiling or by surface abrasion. While soiling can be reverted by cleaning, surface abrasion is a non reversible degradation.The aim of this project was to study the accelerated aging of second surface silvered thickglass solar reflectors under simulated sandstorm conditions and develop a multi-parametric model which relates the specular reflectance loss to dust/sand storm parameters: wind velocity, dust concentration and time of exposure. This project focused on the degradation caused by surface abrasion.Sandstorm conditions were simulated in a prototype environmental test chamber. Material samples (6cm x 6cm) were exposed to Arizona coarse test dust. The dust stream impactedthese material samples at a perpendicular angle. Both wind velocity and dust concentrationwere maintained at a stable level for each accelerated aging test. The total exposure time in the test chamber was limited to 1 hour. Each accelerated aging test was interrupted every 4 minutes to measure the specular reflectance of the material sample after cleaning.The accelerated aging test campaign had to be aborted prematurely due to a contamination of the dust concentration sensor. A robust multi-parametric degradation model could thus not be derived. The experimental data showed that the specular reflectance loss decreasedeither linearly or exponentially with exposure time, so that a degradation rate could be defined as a single modeling parameter. A correlation should be derived to relate this degradation rate to control parameters such as wind velocity and dust/sand concentration.The sandstorm chamber design would have to be updated before performing further accelerated aging test campaigns. The design upgrade should improve both the reliability of the test equipment and the repeatability of accelerated aging tests. An outdoor exposure test campaign should be launched in deserts to learn more about the intensity, frequencyand duration of dust/sand storms. This campaign would also serve to correlate the results of outdoor exposure tests with accelerated exposure tests in order to develop a robust service lifetime prediction model for different types of solar reflector materials.

Modeling precipitation and its effect on recrystallization during hot strip rolling of niobium steels

Using a physically based model, the microstructural evolution of Nb microalloyed steels during rolling in SSAB Tunnplåt’s hot strip mill was modeled. The model describes the evolution of dislocation density, the creation and diffusion of vacancies, dynamic and static recovery through climb and glide, subgrain formation and growth, dynamic and static recrystallization and grain growth. Also, the model describes the dissolution and precipitation of particles. The impeding effect on grain growth and recrystallization due to solute drag and particles is accounted for. During hot strip rolling of Nb steels, Nb in solid solution retards recrystallization due to solute drag and at lower temperatures strain-induced precipitation of Nb(C,N) may occur which effectively retard recrystallization. The flow stress behavior during hot rolling was calculated where the mean flow stress values were calculated using both the model and measured mill data. The model showed that solute drag has an essential effect on recrystallization during hot rolling of Nb steels.

Review of the literature on credit risk modeling : development of the past 10 years

This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Dynamic whole system testing of combined renewable heating systems : the current state of the art

Objective: For the evaluation of the energetic performance of combined renewable heating systems that supply space heat and domestic hot water for single family houses, dynamic behaviour, component interactions, and control of the system play a crucial role and should be included in test methods. Methods: New dynamic whole system test methods were developed based on “hardware in the loop” concepts. Three similar approaches are described and their differences are discussed. The methods were applied for testing solar thermal systems in combination with fossil fuel boilers (heating oil and natural gas), biomass boilers, and/or heat pumps. Results: All three methods were able to show the performance of combined heating systems under transient operating conditions. The methods often detected unexpected behaviour of the tested system that cannot be detected based on steady state performance tests that are usually applied to single components. Conclusion: Further work will be needed to harmonize the different test methods in order to reach comparable results between the different laboratories. Practice implications: A harmonized approach for whole system tests may lead to new test standards and improve the accuracy of performance prediction as well as reduce the need for field tests.

Effective measures to decrease air contaminants through risk and control visualization : a study of the effective use of QR codes to facilitate safety training

Woodworking industries still consists of wood dust problems. Young workers are especially vulnerable to safety risks. To reduce risks, it is important to change attitudes and increase knowledge about safety. Safety training have shown to establish positive attitudes towards safety among employees. The aim of current study is to analyze the effect of QR codes that link to Picture Mix EXposure (PIMEX) videos by analyzing attitudes to this safety training method and safety in student responses. Safety training videos were used in upper secondary school handicraft programs to demonstrate wood dust risks and methods to decrease exposure to wood dust. A preliminary study was conducted to investigate improvement of safety training in two schools in preparation for the main study that investigated a safety training method in three schools. In the preliminary study the PIMEX method was first used in which students were filmed while wood dust exposure was measured and subsequently displayed on a computer screen in real time. Before and after the filming, teachers, students, and researchers together analyzed wood dust risks and effective measures to reduce exposure to them. For the main study, QR codes linked to PIMEX videos were attached at wood processing machines. Subsequent interviews showed that this safety training method enables students in an early stage of their life to learn about risks and safety measures to control wood dust exposure. The new combination of methods can create awareness, change attitudes and motivation among students to work more frequently to reduce wood dust.