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000823106 019__ $$a1005136705$$a1011908725
000823106 020__ $$a9783319592800$$q(electronic book)
000823106 020__ $$a3319592807$$q(electronic book)
000823106 020__ $$z9783319592794
000823106 0247_ $$a10.1007/978-3-319-59280-0$$2doi
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000823106 049__ $$aISEA
000823106 050_4 $$aTA190$$b.I58 2017eb
000823106 08204 $$a620.0068$$223
000823106 1112_ $$aInternational Conference on Management Science and Engineering Management$$n(11th :$$d2017 :$$cKanazawa-shi, Japan)
000823106 24510 $$aProceedings of the Eleventh International Conference on Management Science and Engineering Management /$$cJiuping Xu, Mitsuo Gen, Asaf Hajiyev, Fang Lee Cooke, editors.
000823106 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018]
000823106 264_4 $$c©2018
000823106 300__ $$a1 online resource.
000823106 336__ $$atext$$btxt$$2rdacontent
000823106 337__ $$acomputer$$bc$$2rdamedia
000823106 338__ $$aonline resource$$bcr$$2rdacarrier
000823106 347__ $$atext file$$bPDF$$2rda
000823106 4901_ $$aLecture notes on multidisciplinary industrial engineering
000823106 504__ $$aIncludes bibliographical references and author index.
000823106 5050_ $$aPreface; Organization; Executive Committee; General Chairs; Program Committee Chairs; Organizing Committee Chair; Local Arrangement Committee Chair; Local Arrangement Committee; Program Committee; Secretary-General; Under-Secretary; General; Secretaries; Contents; Advances in Management Science of the Eleventh ICMSEM; Advancement of Computing Methodology, Data Analysis, Enterprise Operation Management and Decision Support System Based on the Eleventh ICMSEM Proceedings; 1 Introduction; 2 Literature Review; 2.1 Computing Methodology; 2.2 Data Analysis; 2.3 Enterprise Operation Management
000823106 5058_ $$a2.4 Decision Support System3 The Central Issues in the Proceedings Volume I; 4 Development Trends for MS and ICMSEM; 4.1 CiteSpace Analysis Results; 4.2 Tendency in the ICMSEM Evaluation; 5 Conclusion; References; Computing Methodology; A Comparison of Pretest, Stein-Type and Penalty Estimators in Logistic Regression Model; 1 Introduction; 2 Model and Estimation Strategies; 2.1 The Unrestricted and Restricted Maximum Likelihood Estimator; 2.2 The Linear Shrinkage Estimator; 2.3 The Preliminary Test Estimator; 2.4 The Shrinkage Pretest Estimator; 2.5 The Stein-Type Shrinkage Estimator
000823106 5058_ $$a2.6 The Positive-Part Stein-Type Shrinkage Estimator2.7 The LASSO Estimator; 2.8 The Ridge Regression Estimator; 3 Monte-Carlo Simulation Studies; 3.1 Model with Correct Candidate Submodel (* =0); 3.2 Model with Correct and Incorrect Candidate Submodel (* 0); 4 Real Data Example: South African Heart Disease Data; 5 Discussion and Conclusions; References; Multi-objective Job Shop Rescheduling with Estimation of Distribution Algorithm; 1 Introduction; 2 Mathematical Formulation; 3 Effective Multiobjectives Estimation of Distribution Algorithm
000823106 5058_ $$a3.1 A Descriptive Analysis of Air Pollution and Death Data3.2 Solution Representation; 3.3 Transition Probability; 3.4 Fitness Assignment Mechanisms; 4 Experiments and Discussion; 4.1 Convergence; 4.2 Distribution Performance; 4.3 Computation Costs; 5 Conclusion; References; Multi-Queue Priority Based Algorithm for CPU Process Scheduling; 1 Introduction; 2 CPU Scheduling; 2.1 Ready Queue Management; 3 Scheduling Algorithms; 3.1 Shortest Job First (SJF); 3.2 Shortest Remaining Time First (SRTF); 3.3 Round Robin (RR); 3.4 Priority Scheduling (PS); 4 Related Work; 5 Proposed Algorithm
000823106 5058_ $$a6 Pseudo Code7 Case Studies; 7.1 Case Study 1; 7.2 Case Study 2; 7.3 Case Study 3; 7.4 Case Study 4 -- Special Case; 8 Results and Discussion; 8.1 Comparison of Average Waiting Time; 8.2 Comparison of Average Turnaround Time; 9 Conclusion and Future Work; References; An Order-Based GA for Robot-Based Assembly Line Balancing Problem; 1 Introduction; 2 Robotic Assembly Line Balancing Problem; 3 Order-Based GA Design; 3.1 Crossover Operators; 3.2 Mutation Operators; 3.3 Fitness Evaluation; 4 Local Search Procedure; 4.1 Task Sequence Search; 4.2 Robot Assignment Search; 5 Numerical Experiments
000823106 506__ $$aAccess limited to authorized users.
000823106 520__ $$aThis book is organized in 2 volumes and 6 parts. Part I is Big Data Analytics, which is about new advances of analysis, statistics, coordination and data mining of big data; Part II is Information Systems Management, which is about the development of big data information system or cloud platform. Part III is Computing Methodology with Big Data, which is about the improvements of traditional computation technologies in the background of big data; Part IV is Uncertainty Decision Making, which is about the decision making methods with various uncertain information, such as fuzzy, random, rough, gray, unascertained. Part V is Intelligence Algorithm. Part VI is Data Security, which is a particularly important aspect in the modern management environment.
000823106 588__ $$aOnline resource; title from PDF title page (viewed July 10, 2017).
000823106 650_0 $$aEngineering$$xManagement$$vCongresses.
000823106 650_0 $$aManagement science$$vCongresses.
000823106 7001_ $$aXu, Jiuping$$c(Professor of management science),$$eeditor.
000823106 7001_ $$aGen, Mitsuo,$$d1944-$$eeditor.
000823106 7001_ $$aHajiyev, Asaf,$$eeditor.
000823106 7001_ $$aCooke, Fang Lee,$$eeditor.
000823106 77608 $$iPrint version: $$z9783319592794
000823106 830_0 $$aLecture notes on multidisciplinary industrial engineering.
000823106 852__ $$bebk
000823106 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-59280-0$$zOnline Access$$91397441.1
000823106 909CO $$ooai:library.usi.edu:823106$$pGLOBAL_SET
000823106 980__ $$aEBOOK
000823106 980__ $$aBIB
000823106 982__ $$aEbook
000823106 983__ $$aOnline
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