4,906 research outputs found

    Comparison of different Multiple-criteria decision analysis methods in the context of conceptual design: application to the development of a solar collector structure

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    At each stage of the product development process, the designers are facing an important task which consists of decision making. Two cases are observed: the problem of concept selection in conceptual design phases and, the problem of pre-dimensioning once concept choices are made. Making decisions in conceptual design phases on a sound basis is one of the most difficult challenges in engineering design, especially when innovative concepts are introduced. On the one hand, designers deal with imprecise data about design alternatives. On the other hand, design objectives and requirements are usually not clear in these phases. The greatest opportunities to reduce product life cycle costs usually occur during the first conceptual design phases. The need for reliable multi-criteria decision aid (MCDA) methods is thus greatest at early conceptual design phases. Various MCDA methods are proposed in the literature. The main criticism of these methods is that they usually yield different results for the same problem. In this work, an analysis of six MCDA methods (weighed sum, weighted product, Kim & Lin, compromise programming, TOPSIS, and ELECTRE I) was conducted. Our analysis was performed via an industrial case of solar collector structure development. The objective is to define the most appropriate MCDA methods in term of three criteria: (i) the consistency of the results, (ii) the ease of understanding and, (iii) the adaptation of the decision type. The results show that TOPSIS is the most consistent MCDA method in our case

    Critical review of multi-criteria decision aid methods in conceptual design phases: application to the development of a solar collector structure

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    At each stage of the product development process, the designers are facing an important task which consists of decision making. Two cases are observed: the problem of concept selection in conceptual design phases and, the problem of pre-dimensioning once concept choices are made. Making decisions in conceptual design phases on a sound basis is one of the most difficult challenges in engineering design, especially when innovative concepts are introduced. On the one hand, designers deal with imprecise data about design alternatives. On the other hand, design objectives and requirements are usually not clear in these phases. The greatest opportunities to reduce product life cycle costs usually occur during the first conceptual design phases. The need for reliable multi-criteria decision aid (MCDA) methods is thus greatest at early conceptual design phases. Various MCDA methods are proposed in the literature. The main criticism of these methods is that they usually yield different results for the same problem [22,23,25]. In this work, an analysis of six MCDA methods (weighed sum, weighted product, Kim & Lin, compromise programming, TOPSIS, and ELECTRE I) was conducted. Our analysis was performed via an industrial case of solar collector structure development. The objective is to define the most appropriate MCDA methods in term of three criteria: (i) the consistency of the results, (ii) the ease of understanding and, (iii) the adaptation of the decision type. The results show that TOPSIS is the most consistent MCDA method in our case

    Determination of the most suitable Technology Transfer Strategy for Wind Turbines using an Integrated AHP-TOPSIS Decision Model

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    The high-speed development of industrial products and goods in the world has caused “technology” to be considered as a crucial competitive advantage for most large organizations. In recent years, developing countries have considerably tended to promote their technological and innovative capabilities through importing high-tech equipment owned and operated by developed countries. There are currently a variety of solutions to transfer a particular technology from a developed country. The selection of the most profitable technology transfer strategy is a very complex decision-making problem for technology importers as it involves different technical, environmental, social, and economic aspects. In this study, a hybrid multiple-criteria decision making (MCDM) model based on the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to evaluate and prioritise various technology transfer strategies for wind turbine systems. For this purpose, a number of criteria and sub-criteria are defined from the viewpoint of wind energy investors, wind turbine manufacturers, and wind farm operators. The relative importance of criteria and sub-criteria with respect to the ultimate goal are computed using the eigenvalue method and then, the technology transfer alternatives are ranked based on their relative closeness to the ideal solution. The model is finally applied to determine the most suitable wind turbine technology transfer strategy among four options of reverse engineering, technology skills training, turn-key contracts, and technology licensing for the renewable energy sector of Iran, and the results are compared with those obtained by classical decision-making models

    30 Years of Software Refactoring Research: A Systematic Literature Review

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd

    30 Years of Software Refactoring Research:A Systematic Literature Review

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    Due to the growing complexity of software systems, there has been a dramatic increase and industry demand for tools and techniques on software refactoring in the last ten years, defined traditionally as a set of program transformations intended to improve the system design while preserving the behavior. Refactoring studies are expanded beyond code-level restructuring to be applied at different levels (architecture, model, requirements, etc.), adopted in many domains beyond the object-oriented paradigm (cloud computing, mobile, web, etc.), used in industrial settings and considered objectives beyond improving the design to include other non-functional requirements (e.g., improve performance, security, etc.). Thus, challenges to be addressed by refactoring work are, nowadays, beyond code transformation to include, but not limited to, scheduling the opportune time to carry refactoring, recommendations of specific refactoring activities, detection of refactoring opportunities, and testing the correctness of applied refactorings. Therefore, the refactoring research efforts are fragmented over several research communities, various domains, and objectives. To structure the field and existing research results, this paper provides a systematic literature review and analyzes the results of 3183 research papers on refactoring covering the last three decades to offer the most scalable and comprehensive literature review of existing refactoring research studies. Based on this survey, we created a taxonomy to classify the existing research, identified research trends, and highlighted gaps in the literature and avenues for further research.Comment: 23 page

    Symbiotic Evolution of Rule Based Classifiers

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