Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A...Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A special multiple-objective genetic algorithm,namely the Nondominated Sorting Genetic AlgorithmⅡ(NSGAⅡ),is used to design responsive orbits.This algorithm has considered the conflicting metrics of orbits to achieve the optimal solution,including the orbital elements and launch programs of responsive vehicles.Low-Earth fast access orbits and low-Earth repeat coverage orbits,two subtypes of responsive orbits,can be designed using NSGAI under given metric tradeoffs,number of vehicles,and launch mode.By selecting the optimal solution from the obtained Pareto fronts,a designer can process the metric tradeoffs conveniently in orbit design.Recurring to the flexibility of the algorithm,the NSGAI promotes the responsive orbit design further.展开更多
Using generalized univex functions, a nondifferentiable multiple-objective optimization problem is considered.Kuhn-Tucker type sufficient optimality conditions are obtained for a feasible point to be an efficient or p...Using generalized univex functions, a nondifferentiable multiple-objective optimization problem is considered.Kuhn-Tucker type sufficient optimality conditions are obtained for a feasible point to be an efficient or properly efficient solution. Mond-Weir type duality programming is constructed,the weak and strong duality theorems are proved.展开更多
This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing e...This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing efficiency and obtaining business synergy. Prior literature suggests that synergies could arise due to taxes, market power or efficiency improvements. This study evaluates the efficiency of M&A in Brazil among publicly-traded companies. We used models with multiple objectives from Goal Programming and Data Envelopment Analysis (GPDEA), employing accounting indicators as input and output variables, and thus evaluated the emergence of synergy gains. These models allow us to analyze and classify the M&A according to the efficiency obtained in such processes. Some of the M&A cases analyzed were mistakenly considered efficient when used traditional models. And, as expected, the GPDEA was proved to be superior to classical models;however it was noticed that few of the cases investigated were proved to be effective. We presented a new application for multi-objective approach that can be used to assess mergers and acquisitions. The dualapplication of GPDEA provided a greater understanding of efficiency generation in synergy creation by means of M&A.展开更多
This paper reviews various inverse analysis models used in steel material design,with a focus on integrating process,microstructure,and properties through advanced machine learning techniques.The study underscores the...This paper reviews various inverse analysis models used in steel material design,with a focus on integrating process,microstructure,and properties through advanced machine learning techniques.The study underscores the importance of establishing comprehensive models that effectively link these elements for enhanced materials engineering.Key models discussed include the convolutional neural network–artificial neural network-coupled model,which employs convolutional neural networks for feature extraction;the Bayesian-optimized generative adversarial network–conditional generative adversarial network model,which generates diverse virtual microstructures;the multi-objective optimization model,which concentrates on process–property relationships;and the microstructure–process parallelization model,which correlates microstructural features with process conditions.Each model is assessed for its strengths and limitations,influencing its practical applicability in material design.The paper concludes by advocating for continued improvements in model accuracy and versatility,with the ultimate goal of enhancing steel properties and expanding the scope of data-driven material development.展开更多
The statistical modeling of extraordinary loads on buildings has been stagnant for decades due to the laborious and error-prone nature of existing survey methods,such as questionnaires and verbal inquiries.This study ...The statistical modeling of extraordinary loads on buildings has been stagnant for decades due to the laborious and error-prone nature of existing survey methods,such as questionnaires and verbal inquiries.This study proposes a new vision-based survey method for collecting extraordinary load data by automatically analyzing surveillance videos.For this purpose,a crowd head tracking framework is developed that integrates crowd head detection and reidentification models based on convolutional neural networks to obtain head trajectories of the crowd in the survey area.The crowd head trajectories are then analyzed to extract crowd quantity and velocities,which are the essential factors for extraordinary loads.For survey areas with frequent crowd movements during temporary events,the equivalent dynamic load factor can be further estimated using crowd velocity to consider dynamic effects.A crowd quantity investigation experiment and a crowd walking experiment are conducted to validate the proposed survey method.The experimental results prove that the proposed survey method is effective and accurate in collecting load data and reasonable in considering dynamic effects during extraordinary events.The proposed survey method is easy to deploy and has the potential to collect substantial and reliable extraordinary load data for determining design load on buildings.展开更多
This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context,...This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers： central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs＇ scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.展开更多
Consistent decision-making requires a structured and systematic evaluation of advantages and disadvantages of different choice possibilities.For transport projects,policies or policy measures,and transport options eva...Consistent decision-making requires a structured and systematic evaluation of advantages and disadvantages of different choice possibilities.For transport projects,policies or policy measures,and transport options evaluation,various multi-criteria methods have been developed and effectively applied to complement conventional cost effectiveness and cost benefit analysis.The present paper aims to present a state-of-the-art review of pertinent literature regarding multi-criteria decision-making(MCD M)in the transport sector,focusing on the basic concepts and procedure for multi-criteria decision-making in the transport sector,along with its role and evaluation parameters.A large selection of over 50 papers and publications between 1982 and 2019 have been reviewed,in order to provide an insight into the uses of MCDM methods in transport applications.Most commonly used MCDM metho ds techniques are identified and discussed through a wide review of pertinent literature,research and case studies,leading to interesting conclusions that provide a valuable insight into the use of multicriteria analysis techniques in transport sector related decision-making.Based on the wide range of reviewed literature,it is concluded that MCDM methods are being applied mostly to evaluate transport options rather than transport policies or projects and the most commonly used MCDM method in transport sector problems are analytic hierarchy process(AHP).展开更多
文摘Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A special multiple-objective genetic algorithm,namely the Nondominated Sorting Genetic AlgorithmⅡ(NSGAⅡ),is used to design responsive orbits.This algorithm has considered the conflicting metrics of orbits to achieve the optimal solution,including the orbital elements and launch programs of responsive vehicles.Low-Earth fast access orbits and low-Earth repeat coverage orbits,two subtypes of responsive orbits,can be designed using NSGAI under given metric tradeoffs,number of vehicles,and launch mode.By selecting the optimal solution from the obtained Pareto fronts,a designer can process the metric tradeoffs conveniently in orbit design.Recurring to the flexibility of the algorithm,the NSGAI promotes the responsive orbit design further.
基金Shandong Science Development Plan Foundation ( NO.JOOP 55)
文摘Using generalized univex functions, a nondifferentiable multiple-objective optimization problem is considered.Kuhn-Tucker type sufficient optimality conditions are obtained for a feasible point to be an efficient or properly efficient solution. Mond-Weir type duality programming is constructed,the weak and strong duality theorems are proved.
文摘This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing efficiency and obtaining business synergy. Prior literature suggests that synergies could arise due to taxes, market power or efficiency improvements. This study evaluates the efficiency of M&A in Brazil among publicly-traded companies. We used models with multiple objectives from Goal Programming and Data Envelopment Analysis (GPDEA), employing accounting indicators as input and output variables, and thus evaluated the emergence of synergy gains. These models allow us to analyze and classify the M&A according to the efficiency obtained in such processes. Some of the M&A cases analyzed were mistakenly considered efficient when used traditional models. And, as expected, the GPDEA was proved to be superior to classical models;however it was noticed that few of the cases investigated were proved to be effective. We presented a new application for multi-objective approach that can be used to assess mergers and acquisitions. The dualapplication of GPDEA provided a greater understanding of efficiency generation in synergy creation by means of M&A.
基金funded by a Grant-in-Aid for Transformative Research Areas 21H05194“Material Creation in Super Field”and 22H01807 from the Japanese Grants-in-Aid for Scientific Research.
文摘This paper reviews various inverse analysis models used in steel material design,with a focus on integrating process,microstructure,and properties through advanced machine learning techniques.The study underscores the importance of establishing comprehensive models that effectively link these elements for enhanced materials engineering.Key models discussed include the convolutional neural network–artificial neural network-coupled model,which employs convolutional neural networks for feature extraction;the Bayesian-optimized generative adversarial network–conditional generative adversarial network model,which generates diverse virtual microstructures;the multi-objective optimization model,which concentrates on process–property relationships;and the microstructure–process parallelization model,which correlates microstructural features with process conditions.Each model is assessed for its strengths and limitations,influencing its practical applicability in material design.The paper concludes by advocating for continued improvements in model accuracy and versatility,with the ultimate goal of enhancing steel properties and expanding the scope of data-driven material development.
基金The authors acknowledge the financial support provided by the National Natural Science Foundation of China(Grant No.52178151).
文摘The statistical modeling of extraordinary loads on buildings has been stagnant for decades due to the laborious and error-prone nature of existing survey methods,such as questionnaires and verbal inquiries.This study proposes a new vision-based survey method for collecting extraordinary load data by automatically analyzing surveillance videos.For this purpose,a crowd head tracking framework is developed that integrates crowd head detection and reidentification models based on convolutional neural networks to obtain head trajectories of the crowd in the survey area.The crowd head trajectories are then analyzed to extract crowd quantity and velocities,which are the essential factors for extraordinary loads.For survey areas with frequent crowd movements during temporary events,the equivalent dynamic load factor can be further estimated using crowd velocity to consider dynamic effects.A crowd quantity investigation experiment and a crowd walking experiment are conducted to validate the proposed survey method.The experimental results prove that the proposed survey method is effective and accurate in collecting load data and reasonable in considering dynamic effects during extraordinary events.The proposed survey method is easy to deploy and has the potential to collect substantial and reliable extraordinary load data for determining design load on buildings.
基金This research is supported by 973 Program under Grant No.2006CB701306
文摘This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers： central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs＇ scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.
基金the European Community’s Seventh Framework Program(FP7/2007-2013)under grant agreement No.611688。
文摘Consistent decision-making requires a structured and systematic evaluation of advantages and disadvantages of different choice possibilities.For transport projects,policies or policy measures,and transport options evaluation,various multi-criteria methods have been developed and effectively applied to complement conventional cost effectiveness and cost benefit analysis.The present paper aims to present a state-of-the-art review of pertinent literature regarding multi-criteria decision-making(MCD M)in the transport sector,focusing on the basic concepts and procedure for multi-criteria decision-making in the transport sector,along with its role and evaluation parameters.A large selection of over 50 papers and publications between 1982 and 2019 have been reviewed,in order to provide an insight into the uses of MCDM methods in transport applications.Most commonly used MCDM metho ds techniques are identified and discussed through a wide review of pertinent literature,research and case studies,leading to interesting conclusions that provide a valuable insight into the use of multicriteria analysis techniques in transport sector related decision-making.Based on the wide range of reviewed literature,it is concluded that MCDM methods are being applied mostly to evaluate transport options rather than transport policies or projects and the most commonly used MCDM method in transport sector problems are analytic hierarchy process(AHP).
