Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Development of an axial flux MEMS BLDC micromotor with increased efficiency and power density

This paper presents a rigorous design and optimization of an axial flux microelectromechanical systems (MEMS) brushless dc (BLDC) micromotor with dual rotor improving both efficiency and power density with an external diameter of only around 10 mm. The stator is made of two layers of windings by MEMS technology. The rotor is developed by film permanent magnets assembled over the rotor yoke. The characteristics of the MEMS micromotor are analyzed and modeled through a 3-D magnetic equivalent circuit (MEC) taking the leakage flux and fringing effect into account. Such a model yields a relatively accurate prediction of the flux in the air gap, back electromotive force (EMF) and electromagnetic torque, whilst being computationally efficient. Based on 3-D MEC model the multi-objective firefly algorithm (MOFA) is developed for the optimal design of this special machine. Both 3-D finite element (FE) simulation and experiments are employed to validate the MEC model and MOFA optimization design

Application of Multi Objective Genetic Algorithm for Optimization of Core Configuration Design of a Fast Breeder Reactor

The optimization problem of nuclear fuel management, reported in the present  study aimed at arriving at the optimal number of subassemblies in the two fuel enrichment zones of the core of a 500 MWe Fast Breeder Reactor. The elitist multi-objective approach of Genetic Algorithm, namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II), was employed in the study. The five parameters considered for optimization are: core excess reactivity, liner heat ratings of inner and outer fuel enrichment zones of the core, fissile material inventory, and breeding ratio. The results obtained from the study indicate that the algorithm is able to produce feasible solutions in an efficient manner while preserving the diversity amongst them. The fast convergence and the diversity-preserving feature of the algorithm are described. The major objective of the work is to study the viability of applying the NSGA-II into the nuclear fuel management problems of fast breeder reactors

Facing-up Challenges of Multiobjective Clustering Based on Evolutionary Algorithms: Representations, Scalability and Retrieval Solutions

Aquesta tesi es centra en algorismes de clustering multiobjectiu, que estan basats en optimitzar varis objectius simultàniament obtenint una col•lecció de solucions potencials amb diferents compromisos entre objectius. El propòsit d'aquesta tesi consisteix en dissenyar i implementar un nou algorisme de clustering multiobjectiu basat en algorismes evolutius per afrontar tres reptes actuals relacionats amb aquest tipus de tècniques. El primer repte es centra en definir adequadament l'àrea de possibles solucions que s'explora per obtenir la millor solució i que depèn de la representació del coneixement. El segon repte consisteix en escalar el sistema dividint el conjunt de dades original en varis subconjunts per treballar amb menys dades en el procés de clustering. El tercer repte es basa en recuperar la solució més adequada tenint en compte la qualitat i la forma dels clusters a partir de la regió més interessant de la col•lecció de solucions ofertes per l’algorisme.Esta tesis se centra en los algoritmos de clustering multiobjetivo, que están basados en optimizar varios objetivos simultáneamente obteniendo una colección de soluciones potenciales con diferentes compromisos entre objetivos. El propósito de esta tesis consiste en diseñar e implementar un nuevo algoritmo de clustering multiobjetivo basado en algoritmos evolutivos para afrontar tres retos actuales relacionados con este tipo de técnicas. El primer reto se centra en definir adecuadamente el área de posibles soluciones explorada para obtener la mejor solución y que depende de la representación del conocimiento. El segundo reto consiste en escalar el sistema dividiendo el conjunto de datos original en varios subconjuntos para trabajar con menos datos en el proceso de clustering El tercer reto se basa en recuperar la solución más adecuada según la calidad y la forma de los clusters a partir de la región más interesante de la colección de soluciones ofrecidas por el algoritmo.This thesis is focused on multiobjective clustering algorithms, which are based on optimizing several objectives simultaneously obtaining a collection of potential solutions with different trade¬offs among objectives. The goal of the thesis is to design and implement a new multiobjective clustering technique based on evolutionary algorithms for facing up three current challenges related to these techniques. The first challenge is focused on successfully defining the area of possible solutions that is explored in order to find the best solution, and this depends on the knowledge representation. The second challenge tries to scale-up the system splitting the original data set into several data subsets in order to work with less data in the clustering process. The third challenge is addressed to the retrieval of the most suitable solution according to the quality and shape of the clusters from the most interesting region of the collection of solutions returned by the algorithm

Preventing premature convergence and proving the optimality in evolutionary algorithms

http://ea2013.inria.fr//proceedings.pdfInternational audienceEvolutionary Algorithms (EA) usually carry out an efficient exploration of the search-space, but get often trapped in local minima and do not prove the optimality of the solution. Interval-based techniques, on the other hand, yield a numerical proof of optimality of the solution. However, they may fail to converge within a reasonable time due to their inability to quickly compute a good approximation of the global minimum and their exponential complexity. The contribution of this paper is a hybrid algorithm called Charibde in which a particular EA, Differential Evolution, cooperates with a Branch and Bound algorithm endowed with interval propagation techniques. It prevents premature convergence toward local optima and outperforms both deterministic and stochastic existing approaches. We demonstrate its efficiency on a benchmark of highly multimodal problems, for which we provide previously unknown global minima and certification of optimality

Sustainability Issues in Benchmarking of Advanced Transit Bus Technologies

From reduced costs to improved efficiency, fleet managers are constantly striving to improve their operations in their transit bus systems. Hybrid electric buses have gained prominence among transit agencies due of their potential for improving fuel economy, reducing costs and increasing reliability over the traditional diesel bus. The question which must be asked is, are hybrid electric buses the best choice for every city? Are there single or multiple solutions which can satisfy the current and future requirements of the transit bus industry? This thesis aims to combine previous research, statistical data and survey results into a multiobjective analysis to determine an answer to these questions. Current and future technologies will be compared with each benefit and downside discussed and scored. For transit agencies looking to justify the significant capital cost increase for new technologies, this research will form the basis for an informed decision

Review of Life Cycle Assessment in Agro-Chemical Processes

Life Cycle Assessment (LCA) is a method used to evaluate the potential impacts on the environment of a product, process, or activity throughout its life cycle. Today’s LCA users are a mixture of individuals with skills in different disciplines who want to evaluate their products, processes, or activities in a life cycle context. This study attempts to present some of the LCA studies on agro-chemical processes, recent advances in LCA and their application on food products and non-food products. Due to the recent development of LCA methodologies and dissemination programs by international and local bodies, use of LCA is rapidly increasing in agricultural and industrial products. The literatures suggest that LCA coupled with other environmental approaches provides much more reliable and comprehensive information to environmentally conscious policy makers, producers, and consumers in selecting sustainable products and production processes. For this purpose, a field study of LCA of biodiesel from Jatropha curcas has been taken as an example in the study. In the past, LCA has been applied primarily to products but recent literature suggests that it has also the potential as an analysis and design tool for processes and services. In general, all primary industries use energy and water resources and emit pollutants gases. LCA is a method to report on and analyze these resource issues across the life cycle of agro-chemical processes. This review has the importance as a first part of a research project to develop a life cycle assessment methodology for agro-chemical industries. It presents the findings of a literature review that focuses on LCA of agriculture and chemical engineering literatur