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001451133 019__ $$a1350689905
001451133 020__ $$a9783031210945$$q(electronic bk.)
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001451133 0247_ $$a10.1007/978-3-031-21094-5$$2doi
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001451133 1112_ $$aBIOMA (Conference)$$n(10th :$$d2022 :$$cMaribor, Slovenia).
001451133 24510 $$aBioinspired optimization methods and their applications :$$b10th international conference, BIOMA 2022, Maribor, Slovenia, November 17-18, 2022 : proceedings /$$cMarjan Mernik, Tome Eftimov, Matej Črepinšek (eds.).
001451133 24630 $$aBIOMA 2022
001451133 264_1 $$aCham :$$bSpringer,$$c[2022]
001451133 264_4 $$c©2022
001451133 300__ $$a1 online resource (x, 277 pages) :$$billustrations (chiefly color).
001451133 336__ $$atext$$btxt$$2rdacontent
001451133 337__ $$acomputer$$bc$$2rdamedia
001451133 338__ $$aonline resource$$bcr$$2rdacarrier
001451133 4901_ $$aLecture notes in computer science ;$$v13627
001451133 500__ $$aInternational conference proceedings.
001451133 500__ $$aIncludes author index.
001451133 5050_ $$aIntro -- Preface -- Organization -- Contents -- An Agent-Based Model to Investigate Different Behaviours in a Crowd Simulation -- 1 Introduction -- 2 The Mathematical Model -- 3 NetLogo Model -- 4 Experimental Results -- 5 Conclusions and Future Works -- References -- Accelerating Evolutionary Neural Architecture Search for Remaining Useful Life Prediction -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Multi-objective Optimization -- 3.2 Speeding up Evaluation -- 4 Experimental Setup -- 4.1 Computational Setup and Benchmark Dataset -- 4.2 Data Preparation and Training Details
001451133 5058_ $$a5 Results -- 6 Conclusions -- References -- ACOCaRS: Ant Colony Optimization Algorithm for Traveling Car Renter Problem -- 1 Introduction -- 2 Related Work -- 3 Problem Description -- 4 ACOCaRS Algorithm -- 5 Experiment -- 5.1 Testbed -- 5.2 Results -- 6 Discussion -- 7 Conclusion and Future Work -- References -- A New Type of Anomaly Detection Problem in Dynamic Graphs: An Ant Colony Optimization Approach -- 1 Introduction -- 2 Anomaly Detection Problem -- 3 Proposed Approach -- 4 Numerical Experiments -- 4.1 Benchmarks -- 4.2 Parameter Setting -- 4.3 Anomaly Detection in Real-World Networks
001451133 5058_ $$a5 Conclusion and Further Work -- References -- .28em plus .1em minus .1emCSS-A Cheap-Surrogate-Based Selection Operator for Multi-objective Optimization -- 1 Introduction -- 2 Background -- 2.1 Spherical Search -- 2.2 Cheap Surrogate Selection (CSS) -- 3 Proposed Method -- 3.1 General Framework of CSS-MOEA -- 3.2 The Detailed Process of CSS-MOEA -- 4 Experiment Results -- 5 Conclusion -- References -- Empirical Similarity Measure for Metaheuristics -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Metaheuristic Algorithms -- 3.2 Benchmark Functions -- 3.3 Parameter Tuning
001451133 5058_ $$a4 Proposed Comparison Method -- 4.1 Algorithm Instances -- 4.2 Algorithm Profiling -- 4.3 Measuring Similarity -- 5 Results -- 5.1 Comparing Instances of the Same Algorithm -- 5.2 Comparing Instances of the Same Tuning Function -- 5.3 Clustering the Algorithms' Instances Based on Similarity -- 5.4 Discussion -- 6 Conclusion -- References -- Evaluation of Parallel Hierarchical Differential Evolution for Min-Max Optimization Problems Using SciPy -- 1 Introduction -- 2 Definition of the Problem -- 3 Differential Evolution for MinMax Problems -- 3.1 Overview of Differential Evolution
001451133 5058_ $$a3.2 Hierarchical (Nested) Differential Evolution and Parallel Model -- 4 Experimental Setup and Results -- 4.1 Benchmark Test Functions -- 4.2 Parameter Settings -- 4.3 Results and Discussion -- 5 Conclusion and Future Work -- References -- Explaining Differential Evolution Performance Through Problem Landscape Characteristics -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 3.1 Benchmark Problem Portfolio -- 3.2 Landscape Data -- 3.3 Algorithm Portfolio -- 3.4 Performance Data -- 3.5 Regression Models -- 3.6 Leave-One Instance Out Validation -- 3.7 SHAP Explanations
001451133 506__ $$aAccess limited to authorized users.
001451133 520__ $$aThis book constitutes the refereed proceedings of the 10th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2022, held in Maribor, Slovenia, in November 2022. The 19 full papers presented in this book were carefully reviewed and selected from 23 submissions. The papers in this BIOMA proceedings specialized in bioinspired algorithms as a means for solving the optimization problems and came in two categories: theoretical studies and methodology advancements on the one hand, and algorithm adjustments and their applications on the other.
001451133 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 23, 2022).
001451133 650_0 $$aNatural computation$$vCongresses.
001451133 650_0 $$aMathematical optimization$$vCongresses.
001451133 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001451133 655_7 $$aConference papers and proceedings.$$2lcgft
001451133 655_0 $$aElectronic books.
001451133 7001_ $$aMernik, Marjan,$$d1964-$$eeditor.
001451133 7001_ $$aEftimov, Tome,$$eeditor.
001451133 7001_ $$aČrepinšek, Matej,$$eeditor.
001451133 77608 $$iPrint version: $$z303121093X$$z9783031210938$$w(OCoLC)1347430700
001451133 830_0 $$aLecture notes in computer science ;$$v13627.
001451133 852__ $$bebk
001451133 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-21094-5$$zOnline Access$$91397441.1
001451133 909CO $$ooai:library.usi.edu:1451133$$pGLOBAL_SET
001451133 980__ $$aBIB
001451133 980__ $$aEBOOK
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