LEADER 00000cam a2200841Mi 4500 
001    859885344 
003    OCoLC 
005    20240129213017.0 
006    m     o  d         
007    cr ||||||||||| 
008    130227s2013    enka    ob    000 0 eng d 
019    849921475|a850168251|a868231732 
020    0124051774 
020    9780124051775 
029 1  AU@|b000053295373 
029 1  AU@|b000059642788 
029 1  AU@|b000062469906 
029 1  DEBBG|bBV041778363 
029 1  DEBBG|bBV043957912 
029 1  DEBBG|bBV044175916 
029 1  DEBSZ|b404328512 
029 1  DEBSZ|b431435804 
029 1  DEBSZ|b481276106 
029 1  GBVCP|b882722913 
029 1  NLGGC|b363380167 
029 1  DKDLA|b820120-katalog:999942427405765 
035    (OCoLC)859885344|z(OCoLC)849921475|z(OCoLC)850168251
       |z(OCoLC)868231732 
040    NLE|beng|erda|epn|cNLE|dB24X7|dCOO|dOCLCO|dCDX|dUMI|dREB
       |dDEBBG|dDEBSZ|dOCLCQ|dOCLCF|dEBLCP|dE7B|dN$T|dGGVRL
       |dOCLCA|dOCLCQ|dOCL|dICA|dAGLDB|dK6U|dZCU|dMERUC|dOCLCQ
       |dU3W|dVTS|dCOCUF|dCEF|dICG|dINT|dOCLCQ|dTKN|dSTF|dOCLCQ
       |dDKC|dAU@|dOCLCQ|dM8D|dOCLCQ|dAJS|dOCLCO|dOCLCQ|dOCLCO 
049    INap 
066    |c(S 
082 04 006.3 
082 04 006.3|223 
099    eBook O’Reilly for Public Libraries 
245 00 Swarm intelligence and bio-inspired computation :|btheory 
       and applications /|cedited by Xin-She Yang, Zhihua Cui, 
       Renbin Xiao, Amir Hossein Gandomi, Mehmet Karamanoglu.
       |h[O'Reilly electronic resource] 
264  1 Oxford :|bElsevier,|c2013. 
300    1 online resource (xxii, 422 pages) :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
490 1  Elsevier insights 
504    Includes bibliographical references. 
505 0  pt. 1. Theoretical aspects of swarm intelligence and bio-
       inspired computing -- pt. 2. Applications and case 
       studies. 
520    Swarm Intelligence and bio-inspired computation have 
       become increasing popular in the last two decades. Bio-
       inspired algorithms such as ant colony algorithms, bat 
       algorithms, bee algorithms, firefly algorithms, cuckoo 
       search and particle swarm optimization have been applied 
       in almost every area of science and engineering with a 
       dramatic increase of number of relevant publications. This
       book reviews the latest developments in swarm intelligence
       and bio-inspired computation from both the theory and 
       application side, providing a complete resource that 
       analyzes and discusses the latest and futu. 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Swarm intelligence. 
650  0 Natural computation. 
650  0 Algorithms. 
650  2 Algorithms 
650  6 Calcul naturel. 
650  6 Algorithmes. 
650  7 algorithms.|2aat 
650  7 Algorithms|2fast 
650  7 Natural computation|2fast 
650  7 Swarm intelligence|2fast 
700 1  Yang, Xin-She,|eeditor. 
700 1  Cui, Zhihua,|eeditor. 
700 1  Xiap, Renbin,|eeditor. 
700 1  Gandomi, Amir Hossein,|eeditor. 
700 1  Karamanoglu, Mehmet,|eeditor. 
776 0  |cHardback|z9780124051638 
830  0 Elsevier insights. 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9780124051638/?ar
       |zAvailalbe on O'Reilly for Public Libraries 
880 8  |6505-00/(S|a5.2.2.3 Time-Dependent Response Threshold 
       Model -- 5.2.3 Some Analysis -- 5.3 Modeling and 
       Simulation of Ant Colony's Labor Division with Multitask -
       - 5.3.1 Background Analysis -- 5.3.2 Design and 
       Implementation of Ant Colony's Labor Division Model with 
       Multitask -- 5.3.2.1 Design of Ant Colony's Labor Division
       Model with Multitask -- Environmental Stimuli -- Agent 
       Attributes -- Probability of Participation and Exit -- 
       Simulation Principle -- 5.3.2.2 Implementation of Ant 
       Colony's Labor Division Model with Multitask -- 5.3.3 
       Supply Chain Virtual Enterprise Simulation -- 5.3.3.1 
       Simulation Example and Parameter Settings -- 5.3.3.2 
       Simulation Results and Analysis -- 5.3.4 Virtual 
       Organization Enterprise Simulation -- 5.3.4.1 Simulation 
       Example and Parameter Settings -- 5.3.4.2 Simulation 
       Results and Analysis -- 5.3.5 Discussion -- 5.4 Modeling 
       and Simulation of Ant Colony's Labor Division with 
       Multistate -- 5.4.1 Background Analysis -- 5.4.2 Design 
       and Implementation of Ant Colony's Labor Division Model 
       with Multistate -- 5.4.2.1 Design of Ant Colony's Labor 
       Division Model with Multistate -- Stimulus Values in 
       Multitask Environment -- Relative Environment Stimulus 
       Value sαβ and Relative Threshold θαβ -- Agent State 
       Transformation -- 5.4.2.2 Implementation of Ant Colony's 
       Labor Division Model with Multistate -- 5.4.3 Simulation 
       Example of Ant Colony's Labor Division Model with 
       Multistate -- 5.4.3.1 Simulation and Experiment 
       Environment -- 5.4.3.2 Parameters of the Simulation Model 
       -- 5.4.3.3 Simulation Results -- 5.4.3.4 Analysis of 
       Results -- 5.5 Modeling and Simulation of Ant Colony's 
       Labor Division with Multiconstraint -- 5.5.1 Background 
       Analysis -- 5.5.2 Design and Implementation of Ant 
       Colony's Labor Division Model with Multiconstraint -- 
       5.5.2.1 Design of Ant Colony's Labor Division Model with 
       Multiconstraint. 
938    Books 24x7|bB247|nbks00054048 
938    Coutts Information Services|bCOUT|n25507109 
938    EBL - Ebook Library|bEBLB|nEBL1207291 
938    ebrary|bEBRY|nebr10704769 
938    EBSCOhost|bEBSC|n486519 
938    Cengage Learning|bGVRL|nGVRL6ZOW 
994    92|bJFN