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Enhancing the sustainability and effectiveness of non-governmental organizations: An integrated neutrosophic decision-making model for determining the most effective corporate governance strategies

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engineering Applications of Artificial Intelligence 2025年 156卷

作者： Emrah Ayhan Hakan Gökhan Gündoğdu Ahmet Aytekin Ahmet Furkan Karakaya Vladimir Simic Dragan Pamucar Department of Political Science and Public Administration Faculty of Economics and Administrative Sciences Anadolu University Tepebaşı 26470 Eskişehir Türkiye Department of Business Administration Hopa Faculty of Economics and Administrative Sciences Artvin Çoruh University Hopa 08100 Artvin Türkiye Public Administration Master Program Graduate Education Institute Anadolu University Tepebaşı 26470 Eskişehir Türkiye University of Belgrade Faculty of Transport and Traffic Engineering Vojvode Stepe 305 11010 Belgrade Serbia Yuan Ze University College of Engineering Department of Industrial Engineering and Management Taoyuan City 320315 Taiwan Department of Computer Science and Engineering College of Informatics Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Mechanics and Mathematics Western Caspian University Baku Azerbaijan İstinye University Faculty of Engineering and Natural Sciences Industrial Engineering Department Sarıyer 34396 İstanbul Türkiye

This research explores the development of effective corporate governance strategies for non-governmental organizations (NGOs) by evaluating both critical decision criteria and innovative organizational models. Based on an extensive literature review, seven governance criteria were identified: credibility and non-profit orientation, regular information flow and transparency, level of institutionalization, frequency of leadership turnover, internal and external stakeholder relations, annual budget, and ideological or religious motivation. In addition, five innovative organizational models were selected as strategic alternatives: continuous learning organization, technology-oriented policy development, income diversification, pluralistic governance, and transformational leadership. The empirical data were gathered through interviews with 16 experts from academia, civil society, and public institutions in Türkiye. To address the complexity and uncertainty of decision-making processes, a hybrid type-2 neutrosophic number (T2NN) multi-criteria decision-making methodology is introduced. The T2NN-ranking comparison and T2NN-criteria importance through intercriteria correlation methods are used to determine the weight of criteria, while T2NN-stable preference ordering towards ideal solution is utilized to rank the alternative models. Results show that the level of institutionalization is the most significant criterion, and income diversification is the most effective organizational model for improving NGO sustainability. The study not only provides practical guidance for NGO leaders but also introduces a robust methodological approach applicable to governance challenges under uncertain conditions.

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Finding minimum volume circumscribing ellipsoids using generalized copositive programming

arXiv

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arXiv 2018年

作者： Mittal, Areesh Hanasusanto, Grani A. Graduate Program in Operations Research and Industrial Engineering University of Texas at Austin United States

We study the problem of finding the Lowner-John ellipsoid, i.e., an ellipsoid with minimum volume that contains a given convex set. We reformulate the problem as a generalized copositive program, and use that reformulation to derive tractable semidefinite programming approximations for instances where the set is defined by affine and quadratic inequalities. We prove that, when the underlying set is a polytope, our method never provides an ellipsoid of higher volume than the one obtained by scaling the maximum volume inscribed ellipsoid. We empirically demonstrate that our proposed method generates high-quality solutions faster than solving the problem to optimality. Furthermore, we outperform the existing approximation schemes in terms of solution time and quality. We present applications of our method to obtain piecewise-linear decision rule approximations for dynamic distributionally robust problems with random recourse, and to generate ellipsoidal approximations for the set of reachable states in a linear dynamical system when the set of allowed controls is a polytope. Copyright © 2018, The Authors. All rights reserved.

关键词： Piecewise linear techniques

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Impact of Scheduling Policies on the Performance of an Additive Manufacturing Production System

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Procedia Manufacturing 2019年 39卷 447-456页

作者： Maaz Saleem Kapadia Binil Starly Alec Thomas Reha Uzsoy Donald Warsing Graduate Program in Operations Research North Carolina State University 2500 Stinson Dr Raleigh NC 27607 USA Edward P.Fitts Department of Industrial and Systems Engineering North Carolina State University 111 Lampe Dr Raleigh NC 27607 USA Poole College of Management North Carolina State University 2801 Founders Dr Raleigh NC 27695 USA

We study the impact of scheduling policies on the cycle time and throughput of an Additive Manufacturing (AM) facility. Orders for irregularly shaped parts with specified due dates and surface quality requirements arrive randomly at the facility. The parts are fabricated in one of several AM build chambers, followed by post-processing operations based on surface finishing requirements. We combine a part placement heuristic with different scheduling policies (FIFO, Earliest Due Date) to allocate parts to AM build chambers and lay out the parts within the chambers to approximately optimize delivery performance. Simulation experiments using an Iterative Optimization-based Simulation (IOS) model integrating a simulation engine (implemented in SIMIO) with a computational engine (implemented in MATLAB) show that the scheduling policies have a significant impact on cycle time and order lateness. Selection and peer review under the responsibility of ICPR25 International Scientific & Advisory and Organizing Committee members.

关键词： Iterative Optimization-based Simulation Additive Manufacturing Genetic Algorithm

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Improved decision rule approximations for multi-stage robust optimization via copositive programming

arXiv

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arXiv 2018年

作者： Xu, Guanglin Hanasusanto, Grani A. Institute for Mathematics and its Applications University of Minnesota MinneapolisMN55455 United States Graduate Program in Operations Research and Industrial Engineering The University of Texas at Austin AustinTX78712-1591 United States

We study decision rule approximations for generic multi-stage robust linear optimization problems. We examine linear decision rules for the case when the objective coefficients, the recourse matrices, and the right-hand sides are uncertain, and examine quadratic decision rules for the case when only the right-hand sides are uncertain. The resulting optimization problems are NP-hard but amenable to copositive programming reformulations that give rise to tight, tractable semidefinite programming solution approaches. We further enhance these approximations through new piecewise decision rule schemes. Finally, we prove that our proposed approximations are tighter than the state-of-the-art schemes and demonstrate their superiority through numerical experiments. Copyright © 2018, The Authors. All rights reserved.

关键词： Linear programming

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Sample size estimation for power and accuracy in the experimental comparison of algorithms

arXiv

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arXiv 2018年

作者： Campelo, Felipe Takahashi, Fernanda Operations Research and Complex Systems Laboratory Universidade Federal de Minas Gerais Belo Horizonte31270-010 Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil

Experimental comparisons of performance represent an important aspect of research on optimization algorithms. In this work we present a methodology for defining the required sample sizes for designing experiments with desired statistical properties for the comparison of two methods on a given problem class. The proposed approach allows the experimenter to define desired levels of accuracy for estimates of mean performance differences on individual problem instances, as well as the desired statistical power for comparing mean performances over a problem class of interest. The method calculates the required number of problem instances, and runs the algorithms on each test instance so that the accuracy of the estimated differences in performance is controlled at the predefined level. Two examples illustrate the application of the proposed method, and its ability to achieve the desired statistical properties with a methodologically sound definition of the relevant sample sizes. Copyright © 2018, The Authors. All rights reserved.

关键词： Sampling

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Tuning metaheuristics by sequential optimization of regression models

arXiv

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arXiv 2018年

作者： Trindade, Áthila R. Campelo, Felipe Operations Research and Complex Systems Laboratory Universidade Federal de Minas Gerais Belo Horizonte31270-010 Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Brazil

Tuning parameters is an important step for the application of metaheuristics to problem classes of interest. In this work we present a tuning framework based on the sequential optimization of perturbed regression models. Besides providing algorithm configurations with good expected performance, the proposed methodology can also provide insights on the relevance of each parameter and their interactions, as well as models of expected algorithm performance for a given problem class, conditional on the parameter values. A test case is presented for the tuning of six parameters of a decomposition-based multiobjective optimization algorithm, in which an instantiation of the proposed framework is compared against the results obtained by the most recent version the Iterated Racing (Irace) procedure. The results suggest that the proposed approach returns solutions that are as good as those of Irace in terms of mean performance, with the advantage of providing more information on the relevance and effect of each parameter on the expected performance of the algorithm. Copyright © 2018, The Authors. All rights reserved.

关键词： Heuristic algorithms

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Improved conic reformulations for K-means clustering

arXiv

引用

arXiv 2017年

作者： Prasad, Madhushini Narayana Hanasusanto, Grani A. Graduate Program in Operations Research and Industrial Engineering University of Texas at Austin United States

In this paper, we show that the popular K-means clustering problem can equivalently be reformulated as a conic program of polynomial size. The arising convex optimization problem is NP-hard, but amenable to a tractable semidefinite programming (SDP) relaxation that is tighter than the current SDP relaxation schemes in the literature. In contrast to the existing schemes, our proposed SDP formulation gives rise to solutions that can be leveraged to identify the clusters. We devise a new approximation algorithm for K-means clustering that utilizes the improved formulation and empirically illustrate its superiority over the state-of-the-art solution schemes. Copyright © 2017, The Authors. All rights reserved.

关键词： K-means clustering

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Robust quadratic programming with mixed-integer uncertainty

arXiv

引用

arXiv 2017年

作者： Mittal, Areesh Gokalp, Can Hanasusanto, Grani A. Graduate Program in Operations Research and Industrial Engineering University of Texas Austin United States

We study robust convex quadratic programs where the uncertain problem parameters can contain both continuous and integer components. Under the natural boundedness assumption on the uncertainty set, we show that the generic problems are amenable to exact copositive programming reformulations of polynomial size. These convex optimization problems are NP-hard but admit a conservative semidefinite programming (SDP) approximation that can be solved efficiently. We prove that the popular approximate S-lemma method—which is valid only in the case of continuous uncertainty—is weaker than our approximation. We also show that all results can be extended to the two-stage robust quadratic optimization setting if the problem has complete recourse. We assess the effectiveness of our proposed SDP reformulations and demonstrate their superiority over the state-of-the-art solution schemes on instances of least squares, project management, and multi-item newsvendor problems. Copyright © 2017, The Authors. All rights reserved.

关键词： Quadratic programming

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Brazilian consumers' preference towards fruits: The drivers of banana, orange, lemon and apple supply chain 7

Brazilian consumers' preference towards fruits: The drivers ...

引用

7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018

作者： Machado, Sivanilza Teixeira Dos Reis, João Gilberto Mendes Da Silva, Adriano Maniçoba Bueno, Régis Cortez Tanaka, Wilson Yoshio De Felice Zampini, Eugenio Toloi, Rodrigo Carlo NAPOLE - Advanced Production Operations Logistics and Strategy Center Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Brazil RESUP - Supply Chain Research Group Post-graduate Program in Production Engineering Paulista University 1212 Dr. Bacelar St. São Paulo SP Brazil iLAB - Image Pattern Recognition Laboratory Federal Institute of São Paulo 1501 Mogi das Cruzes Avenue Suzano SP Singapore

Public health problem is associated to eating habits, such as higher consumption of fast food and popular snakes. Excessive consumption of these foods can cause health problems such as obesity due to its high energy densities. These foods have become commonplace in world culture for their low price and the easy-to-eat foods mass production. It is known that fruits are essential in balanced diets and an important part of the nutrition strategies programs by contribute to a healthy life. Some works has shown a consumer's global trend demand for product and the life quality and between fresh food and healthy. The Brazil are the third in the word in fruit supply chain and one of the biggest problems facing is fruit loss. It is estimated that mean of fruits losses occurs in households. The present study aimed to determine Brazilian preference towards fruit and the Brazilian consumer behavior influence which might contribute to losses during consumption stage. We explored the literature and created a survey with 275 participants, 46% of men and 53% of women, to identify the perception of Brazilian consumers that may contribute to fruit loss. The results shown the consumer preferences in buying mature fruits is associated with habits and can contribute to food losses and waste, because according best practice to fruit preservation is recommended that the majority types of mellow fruits should be stored in refrigerator and some of them should be consume as soon as possible. © ILS 2018 - Information Systems, Logistics and Supply Chain, Proceedings. All rights reserved.

关键词： Citrus fruits

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