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A Coordination-Based Algorithm for Dedicated Destination Vehicle Routing in B2B E-Commerce

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Computer Systems Science & Engineering 2022年第3期40卷 895-911页

作者： Tsung-Yin Ou Chen-Yang Cheng Chun Hsiung Lai hsin-pin fu Department of Marketing and Distribution Management National Kaohsiung University of Science and TechnologyTaiwan Department of Industrial Engineering and Management Taipei University of TechnologyTaiwan Department of Enterprise Information and Industrial Engineering Tunghai UniversityTaiwan

This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing limitations,vehicle destination,*** researchers who previously investigated this problem assumed the vehicle would not return to the depot,but did not consider its final ***,by considering 3PL in the B2B e-commerce,the vehicle is required back to the nearest 3PL location with available *** paper formulates the problem as a mixed integer linear programming(MILP)model with the objective of minimizing the total travel distance.A coordinate representation particle swarm optimization(CRPSO)algorithm is developed to obtain the best delivery sequencing and the capacity of each *** of the computational study show that the proposed method provides solution within a reasonable amount of ***,the result compared to PSO also indicates that the CRPSO is effective.

关键词： Third-party logistics open vehicle routing problem with time windows dedicated destination Notations

Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

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Computer Systems Science & Engineering 2022年第7期42卷 213-227页

作者： hsin-pin fu Tsung-Sheng Chang Chien-Hung Liu Li-Chun Liu Department of Marketing and Distribution Management National Kaohsiung University of Science and TechnologyKaohsiung(824)Taiwan Department of Information Management Da-Yeh UniversityChanghua(515)Taiwan Graduate Institute of Management National Kaohsiung University of Science and TechnologyKaohsiung(824)Taiwan

The advantages of a cloud computing service are cost advantages,availability,scalability,ﬂexibility,reduced time to market,and dynamic access to computing *** can improve the successful adoption rate of cloud computing services if they understand the critical ***ﬁnd critical factors,this studyﬁrst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment ***,a hybrid method that combines two multi-criteria decision-making tools—called the fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the *** results of this study determinedﬁve critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee ***,the paper presents theﬁndings and implications of the study.

关键词： Cloud computing service multi-criteria decision-making critical factors fuzzy analytic network process vlseKriterijumska optimizacija i kompromisno resenje technology-organization-environment

FACTORS OF 3GWC SYSTEMS FOR DRAWING UP CUSTOMIZED STRATEGIES OF PROMOTION

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Journal of Systems Science and Systems Engineering 2011年第3期20卷 365-381页

作者： hsin-pin fu Hwan-Yann SU Fang-Hua WANG Ching-Yi CHANG Hung-Hsuan LEE Department of Marketing and Distribution Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan China Department of Asia-Pacific Industrial and Business Management National University of Kaohsiung Taiwan China Antai College of Economics ＆ Management Shanghai Jiao Tong University Shanghai China Antai College of Economics ＆ Management Shanghai Jiao Tong University Shanghai China Institute of Management National Kaohsiung First University of Science and Technology Taiwan China

This study utilizes fuzzy analytic hierarchy process （FAHP） to analyze decision-making pattems with regard to third-generation wireless communications （3GWC） service adoption, and to provide customized strategic recommendations to suppliers of 3GWC services regarding marketing and resource allocation in the context of the Chinese 3GWC market. First of all, a three-layer hierarchy of 3GWC adoption factors is developed by referring to the relevant literature and industry reports. A questionnaire of pairwise comparisons in the fuzzy AHP format is then designed and distributed to experts familiar with the handset market in Shanghai, China. These surveys are then analyzed using fuzzy AHP to establish an understanding of the weights and impacts of the various factors. The results show that the four most important factors for the adoption of 3GWC systems are：（i） handset price and voice and data-transmission fees; （ii） handset aesthetics; （iii） personalization; and （iv） network coverage. These findings suggest that providers of such services should customize and diversify the content/applications they offer and ensure the speed and reliability of network access. In addition, handset designs should be in accordance with consumer demands. If these steps can be achieved, then consumers will adopt 3GWC services more rapidly.

关键词： 3GWC (third generation mobile) adoption factors FAHP

A Model for Selecting a Biomass furnace Supplier Based on Qualitative and Quantitative Factors

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Computers, Materials & Continua 2021年第11期69卷 2339-2353页

作者： Chia-Nan Wang hsin-pin fu Hsien-pin Hsu Van Thanh Nguyen Viet Tinh Nguyen Ansari Saleh Ahmar Department of Industrial Engineering and Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Department of Marketing and Distribution Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Department of Supply Chain Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Faculty of Commerce Van Lang UniversityHo Chi Minh City70000Vietnam Faculty Department of Statistics Faculty of Mathematics and Natural SciencesUniversitas Negeri MakassarMakassar90223Indonesia

In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy *** energy resource plays a vital role in meeting the energy needs of the world,especially in *** has favorable natural conditions for this energy *** it is hot and humid,and it has much rainfall and fertile soil,biomass develops very ***,byproducts from agriculture and forestry are abundant and continuously ***,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta *** energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable *** advantage of this energy source provides energy for economic development and ensures environmental *** to the abovementioned favorable conditions,many biomass energy plants are being built in *** other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria *** this case,decisionmakers must evaluate many qualitative and quantitative *** factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making ***,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative ***,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-m

关键词： Biomass energy supplier selection biomass furnace MCDM optimization CoCoSo algorithm fuzzy theory FAHP model industry 4.0

An Intelligent Recommendation System for Real Estate Commodity

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Computer Systems Science & Engineering 2022年第9期42卷 881-897页

作者： Tsung-Yin Ou Guan-Yu Lin hsin-pin fu Shih-Chia Wei Wen-Lung Tsai Department of Marketing and Distribution Management National Kaohsiung University of Science and TechnologyKaohsiung824Taiwan College of Management National Kaohsiung University of Science and TechnologyKaohsiung824Taiwan Department of Information Management Asia Eastern University of Science and TechnologyNew Taipei220Taiwan

Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search processrenders it difficult for agents and consumers to understand the status changes ofobjects. In this study, Python is used to write web crawler and image recognitionprograms to capture object information from the web pages of real estate agents;perform data screening, arranging, and cleaning;compare the text of real estateobject information;as well as integrate and use the convolutional neural networkof a deep learning algorithm to implement image recognition. In this study, dataare acquired from two business-to-consumer real estate agency networks, i.e., theSinyi real estate agent and the Yungching real estate agent, and one consumer-toconsumer real estate agency platform, i.e., the, FiveNineOne real estate agent. Theresults indicate that text mining can reveal the similarities and differences betweenthe objects, list the number of days that the object has been available for sale onthe website, and provide the price fluctuations and fluctuation times during thesales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for realestate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differencesbetween their commodities and other businesses in approximately 2 min, as wellas rapidly determine developable objects via comparison results provided by thesystem. Meanwhile, consumers require less time in searching and comparingprices after they have understood the commodity dynamic information, therebyallowing the

关键词： Real estate agency web crawler image comparison text mining deep learning real estate object dynamic recommendation system

Scheduling Flexible Flow Shop in Labeling Companies to Minimize the Makespan

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Computer Systems Science & Engineering 2022年第1期40卷 17-36页

作者： Chia-Nan Wang Hsien-pin Hsu hsin-pin fu Nguyen Ky Phuc Phan Van Thanh Nguyen Department of Industrial Engineering and Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Department of Supply Chain Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Department of Marketing and Distribution Management National Kaohsiung University of Science and TechnologyKaohsiung80778Taiwan Faculty of Industrial Engineering and Management International UniversityHo Chi Minh City70000Vietnam Faculty of Commerce Van Lang UniversityHo Chi Minh City723000Vietnam

In the competitive global marketplace,production scheduling plays a vital role in planning in *** deals directly with the time to output products quickly and with a low production *** research examines case study of a Radio-Frequency Identification labeling department at Avery *** main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late *** study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple *** on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big *** optimization programs are used in this study and compared to determine which method can better solve the company’s *** proposed algorithm is able to improve machine utilization with large-scale problems.

关键词： Scheduling flexibleflowshop sequencedependentsetup just-in-time

An infrared study of Be stars based on ISO SWS01 spectra

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Research in Astronomy and Astrophysics 2009年第7期9卷 770-776页

作者： pin Zhang Zai-Qi fu Cosmic Ray Institute Yunnan University Kunming 650091 China Department of Physics Zhaotong Teachers College Zhaotong 657000 China

The Infrared Space Observatory （ISO） Short-Wavelength Spectrometer （SWS） spectra of 10 Be stars are presented. It can be seen that the Be stars show a diversity in their ISO SWS01 spectral classifications by Kraemer et al., from naked stars, stars associated with dust, stars with warm dust shells, stars with cool dust shells to very red sources. In addition, the Brα/HI（14-6） line flux ratio derived for the sample stars is compared with that of P Cyg, and it is found that the line ratio of Be stars which were investigated show not only lower values as suggested by Waters et al., but also larger values. Therefore, the line ratio cannot be used to judge whether a star is a Be star or not.

关键词： stars circumstellar matter - infrared stars - stars emission-line Be

Horizontal gas mixing in rectangular fluidized bed:A novel method for gas dispersion coefficients in various conditions and distributor designs

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Chinese Journal of Chemical Engineering 2017年第7期25卷 848-861页

作者： Asheesh Nautiyal Chien-Song Chyang pin-Wei Li hsin-Yung Hou Department of Chemical Engineering Chung Yuan Christian UniversityTaoyuan 320TaiwanChina

In a rectangular fluidized bed combustor, the tracer gas is injected continuously into the bed from a point source at the center of the distributor plate. In this study, a general governing equation is formulated for tracer gas dispersion in the bed. An analytical solution is derived to estimate the dispersion coefficients, Dxand Dy, in a horizontal plane. The concentration profiles at different sampling heights with various gas velocities are ***, to estimate the dispersion coefficients, surface fitting of the obtained analytical solution to the experimental data is performed. The dispersion coefficients obtained from this model are compared with those of a conventional model. Additionally, the effect of walls, bed height and gas injection rate on the dispersion coefficients in a horizontal plane is investigated, and the effect of distributor design on the dispersion coefficients in a horizontal plane is investigated with different tracer positions. It is found that Dxand Dyare nearly equivalent at a lower tracer gas ratio of the injected gas to the total gas flow rate. It is also demonstrated that the effect of bed height on Dxis minor. This model is also able to estimate the dispersion coefficients in the case of a multihorizontal nozzle distributor.

关键词： Gas dispersion coefficient Horizontal mixing Wall effect Surface modeling

Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms

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Geoscience Frontiers 2021年第1期12卷 441-452页

作者： pin Zhang Zhen-Yu Yin Yin-fu Jin Tommy HTChan fu-ping Gao Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina School of Civil Engineering&Built Environment Science and Engineering FacultyQueensland University of Technology(QUT)BrisbaneQld4001Australia Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing100190China China School of Engineering Science University of Chinese Academy of SciencesBeijing100049China

Compression index Ccis an essential parameter in geotechnical design for which the effectiveness of correlation is still a *** paper suggests a novel modelling approach using machine learning(ML)*** performance of five commonly used machine learning(ML)algorithms,***-propagation neural network(BPNN),extreme learning machine(ELM),support vector machine(SVM),random forest(RF)and evolutionary polynomial regression(EPR)in predicting Cc is comprehensively investigated.A database with a total number of 311 datasets including three input variables,*** void ratio e0,liquid limit water content wL,plasticity index Ip,and one output variable Cc is first *** algorithm(GA)is used to optimize the hyper-parameters in five ML algorithms,and the average prediction error for the 10-fold cross-validation(CV)sets is set as thefitness function in the GA for enhancing the robustness of ML *** results indicate that ML models outperform empirical prediction formulations with lower prediction *** yields the lowest error followed by BPNN,ELM,EPR and *** the ranges of input variables in the database are large enough,BPNN and RF models are recommended to predict ***,if the distribution of input variables is continuous,RF model is the best ***,EPR model is recommended if the ranges of input variables are *** predicted correlations between input and output variables using five ML models show great agreement with the physical explanation.

关键词： Compressibility Clays Machine learning Optimization Random forest Genetic algorithm