A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.

PCB assembly line assignment:a genetic algorithm approach

Purpose – This paper sets out to study a production-planning problem for printed circuit board (PCB) assembly. A PCB assembly company may have a number of assembly lines for production of several product types in large volume. Design/methodology/approach – Pure integer linear programming models are formulated for assigning the product types to assembly lines, which is the line assignment problem, with the objective of minimizing the total production cost. In this approach, unrealistic assignment, which was suffered by previous researchers, is avoided by incorporating several constraints into the model. In this paper, a genetic algorithm is developed to solve the line assignment problem. Findings – The procedure of the genetic algorithm to the problem and a numerical example for illustrating the models are provided. It is also proved that the algorithm is effective and efficient in dealing with the problem. Originality/value – This paper studies the line assignment problem arising in a PCB manufacturing company in which the production volume is high.

A genetic algorithm approach to optimising component placement and retrieval sequence for chip shooter machines

A chip shooter machine in printed circuit board (PCB) assembly has three movable mechanisms: an X-Y table carrying a PCB, a feeder carrier with several feeders holding components and a rotary turret with multiple assembly heads to pick up and place components. In order to get the minimal placement or assembly time for a PCB on the machine, all the components on the board should be placed in a perfect sequence, and the components should be set up on a right feeder, or feeders since two feeders can hold the same type of components, and additionally, the assembly head should retrieve or pick up a component from a right feeder. The entire problem is very complicated, and this paper presents a genetic algorithm approach to tackle it.

A genetic algorithm to optimise the component placement process in the PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.

A genetic algorithm for the generalised transportation problem

The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency.

Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs reenter to the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the current industrial practices.

XML Presentation of Documents Used for Data Exchange in Management of Genetic Resources

In the global strategy for preservation genetic resources of farm animals the implementation of information technology is of great importance. In this regards platform independent information tools and approaches for data exchange are needed in order to obtain aggregate values for regions and countries of spreading a separate breed. The current paper presents a XML based solution for data exchange in management genetic resources of farm animals’ small populations. There are specific requirements to the exchanged documents that come from the goal of data analysis. Three main types of documents are distinguished and their XML formats are discussed. DTD and XML Schema for each type are suggested. Some examples of XML documents are given also.

Distributed Genetic Algorithm Implementation by Means of Remote Methods Invocation Technique – Java RMI

The aim of this work is distributed genetic algorithm implementation (so called island algorithm) to accelerate the optimum searching process in space of solutions. Distributed genetic algorithm has also smaller chances to fall in local optimum. This conception depends on mutual cooperation of the clients which realize separate working of genetic algorithms on local machines. As a tool for implementation of distributed genetic algorithm, created to produce net's applications Java technology was chosen. In Java technology, there is a technique of remote methods invocation - Java RMI. By means of invoking remote methods it can send objects between clients and server RMI.

Investigation and modelling of tremor reducer with the technology of targeted energy transfer

This thesis presents the study of a two-degree-of-freedom (2 DOF) nonlinear system consisting of two grounded linear oscillators coupled to two separate light weight nonlinear energy sinks of an essentially nonlinear stiffness. In this thesis, Targeted Energy Transfer (TET) and NES concept are introduced. Previous studies and research of Energy pumping and NES are presented. The characters in nonlinear energy pumping have been introduced at the start of the thesis. For the aim to design the application of a tremor reduction assessment device, the knowledge of tremor reduction has also been mentioned. Two main parties have been presented in the research: dynamical theoretic method of nonlinear energy pumping study and experiments of nonlinear vibration reduction model. In this thesis, nonlinear energy sink (NES) has been studied and used as a core attachment for the research. A new theoretic method of nonlinear vibration reduction which with two NESs has been attached to a primary system has been designed and tested with the technology of targeted energy transfer. Series connection and parallel connection structure systems have been designed to run the tests. Genetic algorithm has been used and presented in the thesis for searching the fit components. One more experiment has been tested with the final components. The results have been compared to find out most efficiency structure and components for the theoretic model. A tremor reduction experiment has been designed and presented in the thesis. The experiment is for designing an application for reducing human body tremor. By using the theoretic method earlier, the experiment has been designed and tested with a tremor reduction model. The experiment includes several tests, one single NES attached system and two NESs attached systems with different structures. The results of theoretic models and experiment models have been compared. The discussion has been made in the end. At the end of the thesis, some further work has been considered to designing the device of the tremor reduction.

Long-finned pilot whale population diversity and structure in Atlantic waters assessed through biogeochemical and genetic markers

Acknowledgements. Cetacean samples were collected under the auspices of stranding monitoring programs run by the Sociedade Portuguesa de Vida Selvagem, the Coordinadora para o Estudio dos Mamíferos Mariños (supported by the regional government Xunta de Galicia), the UK Cetacean Strandings Investigation Programme and the Scottish Agriculture College Veterinary Science Division (jointly funded by Defra and the Devolved Governments of Scotland and Wales), the Marine Mammals Research Group of the Institute of Marine Research (Norway), the Museum of Natural History of the Faroe Islands and the International Fund for Animal Welfare Marine Mammal Rescue and Research Program (USA). The authors thank all the members of these institutions and organizations for their assistance with data and sample collection. S.S.M., P.M.F. and M.F. were supported by PhD grants from the Fundação para a Ciência e Tecnologia (POPH/FSE ref SFRH/BD/ 38735/ 2007, SFRH/BD/36766/2007 and SFRH/BD/30240/ 2006, respectively). A.L. was supported by a postdoctoral grant from the Fundação para a Ciência e Tecnologia (ref SFRH/BPD/82407/2011). The work related to strandings and tissue collection in Portugal was partially supported by the SafeSea project EEAGrants PT 0039 (supported by Iceland, Liechtenstein and Norway through the EEA Financial Mechanism), the MarPro project Life09 NAT/PT/000038 (funded by the European Union program LIFE+) and the project CetSenti FCT RECI/AAG-GLO/0470/2012 (FCOMP- 01-0124-FEDER-027472) (funded by the program COMPETE and the Fundação para a Ciência e Tecnologia). G.J.P. thanks the University of Aveiro and Caixa Geral de Depósitos (Portugal) for financial support. The authors acknowledge the assistance of the chemical analysts at Marine Scotland Science with the fatty acid analysis.

Genetic improvement of feed conversion ratio via indirect selection against lipid deposition in farmed rainbow trout (Oncorhynchus mykiss Walbaum)

The research leading to these results has received funding from the European Union's Seventh Framework Programme (KBBE.2013.1.2-10) under grant agreement n° 613611 FISHBOOST. Moreover, the original data collection was supported by the European Union, Project PROGRESS Q5RS-2001-00994. The staff at Tervo station, Ossi Ritola and Tuija Paananen, are highly acknowledged for fish management. A. Ka., A. Ki., S. M., D. H. and K. R. designed research and wrote the paper; A.Ka analyzed the data and had primary responsibility for the final content. All authors have read and approved the manuscript. The authors declare no conflicts of interest.

Long-finned pilot whale population diversity and structure in Atlantic waters assessed through biogeochemical and genetic markers

Acknowledgements. Cetacean samples were collected under the auspices of stranding monitoring programs run by the Sociedade Portuguesa de Vida Selvagem, the Coordinadora para o Estudio dos Mamíferos Mariños (supported by the regional government Xunta de Galicia), the UK Cetacean Strandings Investigation Programme and the Scottish Agriculture College Veterinary Science Division (jointly funded by Defra and the Devolved Governments of Scotland and Wales), the Marine Mammals Research Group of the Institute of Marine Research (Norway), the Museum of Natural History of the Faroe Islands and the International Fund for Animal Welfare Marine Mammal Rescue and Research Program (USA). The authors thank all the members of these institutions and organizations for their assistance with data and sample collection. S.S.M., P.M.F. and M.F. were supported by PhD grants from the Fundação para a Ciência e Tecnologia (POPH/FSE ref SFRH/BD/ 38735/ 2007, SFRH/BD/36766/2007 and SFRH/BD/30240/ 2006, respectively). A.L. was supported by a postdoctoral grant from the Fundação para a Ciência e Tecnologia (ref SFRH/BPD/82407/2011). The work related to strandings and tissue collection in Portugal was partially supported by the SafeSea project EEAGrants PT 0039 (supported by Iceland, Liechtenstein and Norway through the EEA Financial Mechanism), the MarPro project Life09 NAT/PT/000038 (funded by the European Union program LIFE+) and the project CetSenti FCT RECI/AAG-GLO/0470/2012 (FCOMP- 01-0124-FEDER-027472) (funded by the program COMPETE and the Fundação para a Ciência e Tecnologia). G.J.P. thanks the University of Aveiro and Caixa Geral de Depósitos (Portugal) for financial support. The authors acknowledge the assistance of the chemical analysts at Marine Scotland Science with the fatty acid analysis.

Interpreting Human Genetic Variation through Genomics and In Vivo Models

Improvements in genomic technology, both in the increased speed and reduced cost of sequencing, have expanded the appreciation of the abundance of human genetic variation. However the sheer amount of variation, as well as the varying type and genomic content of variation, poses a challenge in understanding the clinical consequence of a single mutation. This work uses several methodologies to interpret the observed variation in the human genome, and presents novel strategies for the prediction of allele pathogenicity.

Using the zebrafish model system as an in vivo assay of allele function, we identified a novel driver of Bardet-Biedl Syndrome (BBS) in CEP76. A combination of targeted sequencing of 785 cilia-associated genes in a cohort of BBS patients and subsequent in vivo functional assays recapitulating the human phenotype gave strong evidence for the role of CEP76 mutations in the pathology of an affected family. This portion of the work demonstrated the necessity of functional testing in validating disease-associated mutations, and added to the catalogue of known BBS disease genes.

Further study into the role of copy-number variations (CNVs) in a cohort of BBS patients showed the significant contribution of CNVs to disease pathology. Using high-density array comparative genomic hybridization (aCGH) we were able to identify pathogenic CNVs as small as several hundred bp. Dissection of constituent gene and in vivo experiments investigating epistatic interactions between affected genes allowed for an appreciation of several paradigms by which CNVs can contribute to disease. This study revealed that the contribution of CNVs to disease in BBS patients is much higher than previously expected, and demonstrated the necessity of consideration of CNV contribution in future (and retrospective) investigations of human genetic disease.

Finally, we used a combination of comparative genomics and in vivo complementation assays to identify second-site compensatory modification of pathogenic alleles. These pathogenic alleles, which are found compensated in other species (termed compensated pathogenic deviations [CPDs]), represent a significant fraction (from 3 – 10%) of human disease-associated alleles. In silico pathogenicity prediction algorithms, a valuable method of allele prioritization, often misrepresent these alleles as benign, leading to omission of possibly informative variants in studies of human genetic disease. We created a mathematical model that was able to predict CPDs and putative compensatory sites, and functionally showed in vivo that second-site mutation can mitigate the pathogenicity of disease alleles. Additionally, we made publically available an in silico module for the prediction of CPDs and modifier sites.

These studies have advanced the ability to interpret the pathogenicity of multiple types of human variation, as well as made available tools for others to do so as well.