Search Results - (((((((ant OR wanti) OR mantic) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

Case Studies in Bayesian Statistical Modelling and Analysis.

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Satellite networking : principles and protocols by Sun, Zhili

Table of Contents: “…Traffic Shaping --…”
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Introduction to imprecise probabilities

Table of Contents: “…When does the interpretation of independence (not) matter? …”
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Basic data analysis for time series with R by Derryberry, DeWayne R.

Table of Contents: “…The Algorithm,…”
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Engineering optimization : an introduction with metaheuristic applications by Yang, Xin-She

Table of Contents: “…Genetic Algorithms -- Simulated Annealing -- Ant Algorithms -- Bee Algorithms -- Particle Swarm Optimization -- Harmony Search -- Firefly Algorithm -- Applications. …”
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OIPE 2012

Table of Contents: “…Optimization of EMI filters for electrical drives in aircraftAdaptive level set method for accurate boundary shape in optimization of electromagnetic systems; Amodified immune algorithm with spatial filtering for multiobjective topology optimisation of electromagnetic devices; Use of compensation theorem for the robustness assessment of electromagnetic devices optimal design; Multi-physics optimisation of an energy harvester device for automotive application; Stochastic modeling error reduction using Bayesian approach coupled with an adaptive Kriging-based model.…”
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Optimization in Engineering Sciences : Approximate and Metaheuristic Methods. by Stefanoiu, Dan

Table of Contents: “…Update through elitist strategy; 2.4.3.4. Update by ants ranking; 2.4.4. Systemic ant colony algorithm; 2.4.5. …”
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Handbook of performability engineering

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Advances in Mechatronics and Control Engineering III : Selected, Peer Reviewed Papers from the 2014 3rd International Conference on Mechatronics and Control Engineering (ICMCE 2014...

Table of Contents: “…Research on Stereo Matching Algorithm in Intelligent Vehicle Application; Researching on the Single Lock Chamber Automatic Layout Algorithm; Rough and Fuzzy Set Based Classification Algorithm on Computer Practice Teaching Evaluation; Scheduling Based on an Ant Colony Algorithm with Crossover Operator; Study of Parameters Configuration in Ant Colony Algorithm; Study on the Soft Time Windows Vehicle Synthesis Algorithm Based on Genetic; A New Forecasting Model of Fuzzy Time Series; An Improved Forecasting Model of Fuzzy Time Series; Key Technology in a Lightweight WPF-Based Electronic Map Engine.…”
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Open innovation : new product development essentials from the PDMA

Table of Contents: “…Pricing Algorithm --…”
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High performance programming for soft computing

Table of Contents: “…Chapter 9: A Compendium of Artificial Immune SystemsChapter 10: Applications of Artificial Immune Algorithms; Chapter 11: A Parallel Implementation ofthe NSGA-II; Chapter 12: High-performance Navigation System for Mobile Robots; Chapter 13: A Method Using a Combination of Ant Colony Optimization Variants with Ant Set Partitioning; Chapter 14: Variants of Ant Colony Optimization: A Metaheuristic for Solving the Traveling Salesman Problem; Chapter 15: Quantum Computing; Color Plate Section; Back Cover.…”
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Evolutionary Computing in Advanced Manufacturing. by Tiwari, Manoj

Table of Contents: “…Cover; Half Title page; Title page; Copyright page; Preface; List of Contributors; Chapter 1: Production Planning Using Genetic Algorithm; 1.1 Introduction; 1.2 Production Planning Models; 1.3 Genetic Algorithm; 1.4 Implementation of GA; 1.5 Summary; Further Reading; Chapter 2: Process Planning through Ant Colony Optimization; 2.1 Introduction; 2.2 Ant Colony Optimization (ACO); References; Chapter 3: Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning; 3.1 Introduction; 3.2 Process Planning; 3.3 Machine Set-up Time; 3.4 Chromosome Representation.…”
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Introduction to Mathematical Optimization : From Linear Programming to Metaheuristics. by Yang, Xin-She

Table of Contents: “…Tabu Search""; ""8.1 Tabu Search""; ""8.2 Travelling Salesman Problem""; ""8.3 Tabu Search for TSP""; ""9. Ant Colony Optimization""; ""9.1 Behaviour of Ants""; ""9.2 Ant Colony Optimization""; ""9.3 Double Bridge Problem""; ""9.4 Multi-Peak Functions""; ""10. …”
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Stochastic global optimization : techniques and applications in chemical engineering

Table of Contents: “…Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. …”
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Understanding Artificial Intelligence. by Sabouret, Nicolas

Table of Contents: “…Small but Strong: Understanding How Ants Find Their Way -- Multi-Agent Systems -- The Algorithm and the Ant -- Just Like in the Ant Colony -- Calculating a Path With Ants -- The More the Merrier! …”
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Computational mechanics of discontinua by Munjiza, Antonio A.

Table of Contents: “…Front Matter -- Introduction to Mechanics of Discontinua -- Methods of Mechanics of Discontinua -- Disc to Edge Contact Interaction in 2D -- Triangle to Edge Contact Interaction in 2D -- Ball to Surface Contact Interaction in 3D -- Tetrahedron to Points Contact Interaction in 3D -- Tetrahedron to Triangle Contact Interaction in 3D -- Rock Joints -- MR Contact Detection Algorithm for Bodies of Similar Size -- MR Contact Detection Algorithm for Bodies of Different Sizes -- MR Contact Detection Algorithm for Complex Shapes in 2D -- MR Contact Detection Algorithm for Complex Shapes in 3D -- Parallelization.…”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Generalized Network Design Problems : Modeling and Optimization. by Pop, Petrică C.

Table of Contents: “…3.2 An efficient transformation of the GTSP into the TSP3.3 An exact algorithm for the Generalized Traveling Salesman Problem; 3.4 Integer programming formulations of the GTSP; 3.4.1 Formulations based on the properties of Hamiltonian tours; 3.4.2 Flow based formulations; 3.4.3 A local-global formulation; 3.5 Solving the Generalized Traveling Salesman Problem; 3.5.1 Reinforcing ant colony system for solving the GTSP; 3.5.2 Computational results; 3.5.3 A hybrid heuristic approach for solving the GTSP; 3.5.4 Computational results; 3.6 The drilling problem; 3.6.1 Stigmergy and autonomous robots.…”
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Evolutionary optimization

Table of Contents: “…Cover -- Contents -- Preface -- Contributing Authors -- Part I Introduction -- 1 Conventional Optimization Techniques -- 1 Classifying Optimization Models -- 2 Linear Programming -- 3 Goal Programming -- 4 Integer Programming -- 5 Nonlinear Programming -- 6 Simulation -- 7 Further Reading -- 2 Evolutionary Computation -- 1 What Is Evolutionary Computation -- 2 A Brief Overview of Evolutionary Computation -- 3 Evolutionary Algorithm and Generate-and-Test Search Algorithm -- 4 Search Operators -- 5 Summary -- Part II Single Objective Optimization -- 3 Evolutionary Algorithms and Constrained Optimization -- 1 Introduction -- 2 General considerations -- 3 Numerical optimization -- 4 Final Remarks -- 4 Constrained Evolutionary Optimization -- 1 Introduction -- 2 The Penalty Function Method -- 3 Stochastic Ranking -- 4 Global Competitive Ranking -- 5 How Penalty Methods Work -- 6 Experimental Study -- 7 Conclusion -- Appendix: Test Function Suite -- Part III Multi-Objective Optimization -- 5 Evolutionary Multiobjective Optimization -- 1 Introduction -- 2 Definitions -- 3 Historical Roots -- 4 A Quick Survey of EMOO Approaches -- 5 Current Research -- 6 Future Research Paths -- 7 Summary -- 6 MEA for Engineering Shape Design -- 1 Introduction -- 2 Multi-Objective Optimization and Pareto-Optimality -- 3 Elitist Non-dominated Sorting GA (NSGA-II) -- 4 Hybrid Approach -- 5 Optimal Shape Design -- 6 Simulation Results -- 7 Conclusion -- 7 Assessment Methodologies for MEAs -- 1 Introduction -- 2 Assessment Methodologies -- 3 Discussion -- 4 Comparing Two Algorithms: An Example -- 5 Conclusions and Future Research Paths -- Part IV Hybrid Algorithms -- 8 Hybrid Genetic Algorithms -- 1 Introduction -- 2 Hybridizing GAs with Local Improvement Procedures -- 3 Adaptive Memory GA's -- 4 Summary -- 9 Combining choices of heuristics -- 1 Introduction -- 2 GAs and parameterised algorithms -- 3 Job Shop Scheduling -- 4 Scheduling chicken catching -- 5 Timetabling -- 6 Discussion and future directions -- 10 Nonlinear Constrained Optimization -- 1 Introduction -- 2 Previous Work -- 3 A General Framework to look for SPdn -- 4 Experimental Results -- 5 Conclusions -- Part V Parameter Selection in EAs -- 11 Parameter Selection -- 1 Introduction -- 2 Parameter tuning vs. parameter control -- 3 An example -- 4 Classification of Control Techniques -- 5 Various forms of control -- 6 Discussion -- Part VI Application of EAs to Practical Problems -- 12 Design of Production Facilities -- 1 Introduction -- 2 Design for Material Flow When the Number of I/O Points is Unconstrained -- 3 Design for Material Flow for a Single I/O Point -- 4 Considering Intradepartmental Flow -- 5 Material Handling System Design -- 6 Concluding Remarks -- 13 Virtual Population and Acceleration Techniques -- 1 Introduction -- 2 Concept of Virtual Population -- 3 Solution Acceleration Techniques -- 4 Accelerated GA and Acceleration Sche.…”
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Ivor Horton's beginning Visual C++ 2012 by Horton, Ivor

Table of Contents: “…When to Overload Functions --…”
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