A service oriented architecture for engineering design

Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithms (MOGAs) are well suited to implementation in a Service Oriented Architecture. Often the evaluation process of the MOGA is compute-intensive due to the use of a complex computer model to represent the real-world system. The emerging paradigm of Grid Computing offers a potential solution to the compute-intensive nature of this objective function evaluation, by allowing access to large amounts of compute resources in a distributed manner. This paper presents a grid-enabled framework for multi-objective optimisation using genetic algorithms (MOGA-G) to aid decision making in engineering design

Evolutionary multiobjective optimization in engineering management: an empirical study on bridge deck rehabilitation

There exist multiple objectives in engineering management such as minimum cost and maximum service capacity. Although solution methods of multiobjective optimization problems have undergone continual development over the past several decades, the methods available to date are not particularly robust, and none of them performs well on the broad classes. Because genetic algorithms work with a population of points, they can capture a number of solutions simultaneously, and easily incorporate the concept of Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with the rehabilitation planning of bridge decks at a network level by minimizing the rehabilitation cost and deterioration degree simultaneously

Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering

This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating conditions. In this paper, a design of a basic MOGA which copes successfully with a range of typical chemical engineering optimization problems is considered and the key points of its architecture described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome. Four mathematical functions were used as a test bench. The MOGA was able to find the optimal solution for each objective function, as well as an important number of Pareto optimal solutions. Then, the results of two multiobjective case studies in batch plant design and retrofit were presented, showing the flexibility and adaptability of the MOGA to deal with various engineering problems

Genetic Engineering Online Lessons Improve Teaching and Increase Knowledge and Accepting Attitudes Among Students

Genetic engineering has been used in the production of food in the U.S. for nearly three decades, however, science literacy in genetic engineering among consumers is still low. To address this problem, an online resource called The Journey of a Gene (passel.unl.edu/ge) was created to help incorporate genetic engineering education in high school and college curriculums. Here we report two studies conducted to evaluate the effectiveness of The Journey of a Gene in 1) improving student knowledge and attitudes about genetic engineering and 2) helping teachers increase their knowledge as well as quantity and quality of genetic engineering instruction. In the first study, we surveyed nearly 900 students and found that the online resource was effective in increasing student knowledge and shifting student attitudes to become more accepting of genetic engineering technology. This increase in accepting attitudes varied by gender, background, and trust in government safety regulation. Our results demonstrate that genetic engineering attitudes are not static, but can become more positive through education. In the second study, we demonstrate how The Journey of a Gene addresses common teaching barriers to help six Nebraska high school agriculture teachers a) increase the time spent on genetic engineering in the classroom, b) improve the quality of genetic engineering learning as measured by a shift from learning the controversy to learning the scientific process, enabling students to evaluate the controversy, and c) improve teacher knowledge of genetic engineering. Based on these positive outcomes, we suggest that future funding be allocated to equipping and training teachers in genetic engineering education. Education is a key component to help consumers make informed decisions about purchasing products derived through genetic engineering and make societal decisions about advancing genetic engineering research. Adviser: Donald J. Le

Xenopus: An ideal system for chemical genetics

Chemical genetics, or chemical biology, has become an increasingly powerful method for studying biological processes. The main objective of chemical genetics is the identification and use of small molecules that act directly on proteins, allowing rapid and reversible control of activity. These compounds are extremely powerful tools for researchers, particularly in biological systems that are not amenable to genetic methods. In addition, identification of small molecule interactions is an important step in the drug discovery process. Increasingly, the African frog Xenopus is being used for chemical genetic approaches. Here, we highlight the advantages of Xenopus as a first-line in vivo model for chemical screening as well as for testing reverse engineering approaches. genesis 50:207–218, 2012. © 2012 Wiley Periodicals, Inc

Real-time co-ordinated scheduling using a genetic algorithm

Real-time co-ordination is an emerging approach to operational engineering management aimed at being more comprehensive and widely applicable than existing approaches. Schedule management is a key characteristic of operational co-ordination related to managing the planning and dynamic assignment of tasks to resources, and the enactment of the resulting schedules, throughout a changeable process. This paper presents the application of an agent-oriented system, called the Design Co-ordination System, to an industrial case study in order to demonstrate the appropriate use of a genetic algorithm for the purpose of real-time scheduling. The application demonstrates that real-time co-ordinated scheduling can provide significant reductions in time to complete the computational design process

Optimization of Loaded Meshed Face Gears Design using Genetic Algorithm

This paper present the design strategy for optimization of loaded meshed face gear set. Genetic algorithms are being widely used for optimization, search and neural network synthesis. A lot of work has been conducted using genetic algorithm for different engineering problems related to scheduling and process planning in industrial engineering, network optimization in computer engineering. The work dissertation deals with the optimization of loaded meshed face gear sets using genetic algorithm. Attention is focused on reducing the pressure of gear set subjected to constraints on the maximum pressure, contact location, pressure at slice 1 and pressure at slice 11. The optimum gear set using Genetic Algorithm calculate the pressure. Keywords:Genetic algorithm, loaded meshed face gear, optimization