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Optimizing the configuration of personalized service supply chain under resource orchestration mechanism

ELECTRONIC COMMERCE RESEARCH 2023年 1-42页

作者： Wang, Mozhu Yao, Jianming Beijing Univ Posts & Telecommun Sch Mordern Post Beijing Peoples R China Renmin Univ China Sch Business Beijing Peoples R China

Since customers' demands usually exhibit a greater degree of diversity and personalization, and suppliers' service capacity fluctuates dynamically, the disruptions of service supply chain (SSC) will occur when focal firm cannot find appropriate suppliers that completely meet customers' requirements at specific time and place. To address this challenge, a novel SSC resource orchestration mechanism has been proposed based on large-scale researches on Chinese service enterprises. From the theoretical lens of viability supply chain framework and resource orchestration theory, the process of service suppliers reconstructing their capabilities has been scrutinized. On this basis, this study formulates the optimization model for SSC configuration which captures a trade-off between profitability and service quality, and adopts the improved nsga-ii algorithm to solve the bi-objective optimization model. For verification and validation of the proposed mechanism and algorithm, the presented methodology has been applied in a real-business case of a Chinese leading transportation technologies consulting service enterprise. This study demonstrates that a more flexible and profitable SSC can be reached in the changing business environment through the reconstruction of suppliers' capability and the reconfiguration of the entire supply chain. Besides, all the participants can benefit from the configuration schemes since the interest-sharing strategy has been considered in the optimization model.

关键词： Service supply chain management Resource orchestration mechanism nsga-ii algorithm Supply chain configuration

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Evaluation of the economic statistical design of the multivariate T² control chart with multiple variable sampling intervals scheme: nsga-ii approach

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2015年第12期85卷 2442-2455页

作者： Seif, Asghar Faraz, Alireza Sadeghifar, Magide Islamic Azad Univ Hamedan Branch Dept Math Hamadan Iran Univ Liege HEC Management Sch B-4000 Liege Belgium Bu Ali Sina Univ Dept Stat Hamadan Iran

The economic and statistical merits of a multiple variable sampling intervals scheme are studied. The problem is formulated as a double-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the economic objective. Bai and Lee's [An economic design of variable sampling interval over bar X control charts. Int J Prod Econ. 1998;54:57-64] economic model is considered. Then we find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the non-dominated sorting genetic algorithm. Through an illustrative example, the advantages of the proposed approach are shown by providing a list of viable optimal solutions and graphical representations, which indicate the advantage of flexibility and adaptability of our approach.

关键词： multivariate T-2 control chart nsga-ii algorithm multi-objective optimization economic statistical design variable sampling intervals scheme

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Multi-objective evolutionary approach to select security solutions

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CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY 2017年第2期2卷 64-67页

作者： Lee, Yunghee Choi, Tae Jong Ahn, Chang Wook Gwangju Inst Sci & Technol GIST Sch Elect Engn & Comp Sci 123 Cheomdangwagi Ro Gwangju South Korea Sungkyunkwan Univ Dept Comp Engn 2066 Seobu Ro Suwon South Korea

In many companies or organisations, owners want to deploy the most efficient security solutions at a low cost. The authors propose a way of choosing the optimised security method from many security methods by multi-objective genetic algorithm (GA) considering cost and weakness decrease in this study. The proposed system can find the best security methods in various aspects of security issues. This study uses the nsga-ii algorithm, which has been authorised in a variety of fields, to provide a comparison with old GAs. Their scheme has increased the dominant area by more than 30% compared with the previous scheme and can provide a more diverse solution set.

关键词： genetic algorithms Pareto optimisation evolutionary computation multiobjective evolutionary approach efficient security solutions optimised security method security methods weakness decrease security issues nsga-ii algorithm diverse solution

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Beam dynamics study of the photoinjector at Wuhan advanced light source

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Radiation Detection Technology and Methods 2024年第3期8卷 1319-1332页

作者： Ze-Yi Dai Yuan-Cun Nie Jian-Hua Zhong Lan-Xin Liu Zi-Shuo Liu Jia-Bao Guan Ji-Ke Wang Yuan Chen Ye Zou Hao-Hu Li Jian-Hua He The Institute for Advanced Studies Wuhan UniversityWuhan430072China

Background A full-energy LINAC is under development at Wuhan Advanced Light Source(WALS)to provide beams for the 1.5 GeV storage ring proposed as a fourth-generation synchrotron radiation light source and a future free electron laser(FEL)*** LINAC starts from a photoinjector that is able to produce electron beams with low emittance(<1 mm·mrad),small relative energy spread(<0.5%),and high bunch charge(~1 nC).Purpose and methods To minimize the output emittance and RMS bunch length for the purpose of improving the photoinjector brightness,the influence of different laser pulse profiles on the slice emittance is investigated,and the beam dynamics simulation is performed with non-dominated sorting genetic algorithm-ii(nsga-ii)combining with ASTRA code to find the optimal solution at a bunch charge of 1 *** and conclusion In this paper,the beam dynamics optimization of the photoinjector is presented in detail;the simulation results imply that the laser pulse profile with 1σtruncated Gaussian distribution in transverse and flat-top-like temporal distribution is beneficial to the improvement of beam brightness of the photoinjector,which shows an output emittance of 0.63 mm·mrad in the case of intrinsic thermal emittance of 0.43 mm·mrad.

关键词： Photoinjector Beam dynamics optimization Beam emittance Driving laser nsga-ii algorithm

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Multi-objective evolutionary optimization for visual data mining with virtual reality spaces:: Application to Alzheimer gene expressions

Multi-objective evolutionary optimization for visual data mi...

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8th Annual Genetic and Evolutionary Computation Conference

作者： Valdes, Julio J. Barton, Alan J. Natl Res Council Canada Inst Informat Technol M501200 Montreal Rd Ottawa ON K1A 0R6 Canada

ISBN: (纸本)9781595931863

This paper introduces a multi-objective optimization approach to the problem of computing virtual reality spaces for the visual representation of relational structures (e.g. databases), symbolic knowledge and others, in the context of visual data mining and knowledge discovery. Procedures based on evolutionary computation are discussed. In particular, the nsga-ii algorithm is used as a framework for an instance of this methodology;simultaneously minimizing Sammon's error for dissimilarity measures, and mean cross-validation error on a k-nn pattern classifier. The proposed approach is illustrated with an example from genomics (in particular, Alzheimer's disease) by constructing virtual reality spaces resulting from multi-objective optimization. Selected solutions along the Pareto front approximation are used as nonlinearly transformed features for new spaces that compromise similarity structure preservation (from an unsupervised perspective) and class separability (from a supervised pattern recognition perspective), simultaneously. The possibility of spanning a range of solutions between these two important goals, is a benefit for the knowledge discovery and data understanding process. The quality of the set of discovered solutions is superior to the ones obtained separately, from the point of view of visual data mining.

关键词： visual data mining virtual reality spaces multi-objective optimization genetic algorithms nsga-ii algorithm k-nn classification cross-validation error similarity structure preservation non-linear mapping Sammon error Alzheimer disease genomics

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Cost and Availability Optimization of Overspeed Protection System in a Power Plant

Cost and Availability Optimization of Overspeed Protection S...

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International Conference on Advanced Electrical Engineering (ICAEE)

作者： Mellal, Mohamed Arezki Chebouba, Billal Nazim MHamed Bougara Univ Fac Engn Sci FSI LMSS Boumerdes Algeria

ISBN: (纸本)9781728122205

This paper addresses the cost and availability optimization of an overspeed protection system in a power plant. The literature has only treated the reliability or cost of this system as a single-objective. Therefore, the multi-objective optimization problem considering the availability and cost is presented. The Non-dominated Sorting Genetic algorithm ii (nsga-ii) is applied to generate the Pareto front. The numerical results are discussed under two scenarios of minimum allowable availability.

关键词： Overspeed protection power plant availability cost multi-objective optimization nsga-ii algorithm

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Towards optimization of Availability and Cost in Selection of Geo-distributed Clouds Datacenter 10

Towards optimization of Availability and Cost in Selection o...

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10th IEEE International Conference on Application of Information and Communication Technologies (AICT)

作者： Ziafat, Hasan Babamir, Seyed Morteza Univ Kashan Dept Comp Kashan Iran

ISBN: (纸本)9781509018413

With increasing data clouds in different geographical areas, the availability of a datacenter and the cost of using the datacenter are two concerned factors of clouds users. The present research aims to present a method using K-means clustering and nsga-ii multi-objective algorithm to maximize availability and minimizes cost in selecting a datacenter. The proposed approach was applied to some real geographically distributed datacenters. Results showed that proposed approach outperforms greedy and random common algorithms.

关键词： Geo-distributed Datacenter Clustering the K-means algorithm Multi-Objective Optimizing algorithm nsga-ii algorithm

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Research on Optimal Storage Scheme of Containers in the Port Yard Based on Hydrodynamics 6

Research on Optimal Storage Scheme of Containers in the Port...

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6th International Symposium on Project Management (ISPM)

作者： Dong, Hongjin Zhang, Qi Beijing Jiaotong Univ Sch Traff & Transportat 3 Shangyuancun Beijing 100044 Peoples R China

ISBN: (纸本)9781921712661

This paper converts the container arriving at the port into a truck flow using the theory and method of fluid mechanics, and then to analyze the truck flow's running state on the road. Taking the capacity of the port yard as a "valve" to regulate the flow of container trucks, the running state of the truck flow is changed by adjusting the number of containers entering and exiting the yard. On this basis, a multi-objective optimization model is constructed with the objective of the shortest distribution time and minimum storage cost for containers, so as to obtain the optimal container storage plan. Designing the improved nsga-ii algorithm to solve the model. An empirical research was carried out on the Phase ii terminal of Ningbo Beilun port. And results of this paper verify the accuracy and effectiveness of the model and algorithm.

关键词： container yard capacity fluid mechanics multi-objective optimization nsga-ii algorithm pareto solution

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Design of the hybrid harmonic filter to improve power quality of the grid connected hybrid renewable energy system

Design of the hybrid harmonic filter to improve power qualit...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Assi, Amirhossein Tafreshi, Seyed Masoud Moghaddas Inst Higher Educ Sardar Jangal Rasht Iran Univ Guilan Dept Elect Engn Rasht Iran

ISBN: (纸本)9781728147215

With advancement of technology, renewable energy sources have become more economical, and network loads have become more sensitive to power quality. Renewable Energy systems due to the voltage converters used in their structure, cause power quality problems such as harmonic distortion in the power grid. And also increasing the penetration of Renewable Energy Sources can increase power quality problems. In this paper to improve power quality of the renewable energy system, a parallel hybrid harmonic filter is proposed. The hybrid harmonic filter is a combination of active and passive filter that work together to compensate harmonics in the renewable energy system. In the hybrid filter, size and number of passive filters, hysteresis bandwidth and PI controller gains of the active filter, are optimized by nsga-ii algorithm. The results show performance of the proposed hybrid harmonic filter.

关键词： Harmonic Distortion nsga-ii algorithm Hybrid harmonic filter renewable energy system power quality

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A Multi-objective Optimization Framework to Design Soft-Error-Immune Circuit 19

A Multi-objective Optimization Framework to Design Soft-Erro...

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19th European Conference on Radiation and Its Effects on Components and Systems (RADECS)

作者： Li, Yan Han, Jun Han, Yuanyuan Zeng, Xiaoyoung Zeng, Xiaoyang Fudan Univ Sch Microelect State Key Lab ASIC & Syst Shanghai Peoples R China

ISBN: (纸本)9781728156996

It is widely accepted that Triple Module Redundancy (TMR) hardened method is one of the most effective approach to protect circuit from soft error. However, while the mitigation of Soft Error Rate (SER) entails the inevitable sacrifice of area and power, little attention has been drawn to an optimization method to explore a trade-off between area, power and SER. Thus, with the help of neural network algorithm and nsga-ii algorithm, this study investigates a multi-objective optimization model as a guidance on Soft-Error-Immune circuit design.

关键词： Triple Module Redundancy soft error multiobjective optimization neural network algorithm nsga-ii algorithm radiation hardening by design

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