Search Results - (((((((ant OR alter) OR wantsa) OR parted) OR cantor) OR anne) OR ayant) OR partes) algorithms.

Ant Colony Optimization and Constraint Programming. by Solnon, Christine

Table of Contents: “…Constraint-based local search; 7.4. Discussion; PART II. ANT COLONY OPTIMIZATION; Introduction to Part II.…”
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Theory of randomized search heuristics : foundations and recent developments

Table of Contents: “…Runtime Analysis of Evolutionary Algorithms for Discrete Optimization Peter S. Oliveto and Xin Yao; 3. …”
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Stabilisation and Motion Control of Unstable Objects by Formalʹskiĭ, A. M. (Aleksandr Moiseevich)

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Parts-feeding systems for assembly : organisation, logistics and automation

Table of Contents: “…Cover; Editorial; Kanban-driven parts feeding within a semiautomated O-shaped assembly line: a case study in the automotive industry; Re-balancing problem for assembly lines: new mathematical model and exact solution method; A Changeover Time Reduction through an integration of lean practices: a case study from pharmaceutical sector; Planning models for continuous supply of parts in assembly systems; A decision model for kitting and line stocking with variable operator walking distances; Advances in assembly line parts feeding policies: a literature review.…”
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Bioinformatics algorithms : techniques and applications

Table of Contents: “…BIOINFORMATICS ALGORITHMS; CONTENTS; Preface; Contributors; 1 Educating Biologists in the 21st Century: Bioinformatics Scientists versus Bioinformatics Technicians; PART I TECHNIQUES; 2 Dynamic Programming Algorithms for Biological Sequence and Structure Comparison; 3 Graph Theoretical Approaches to Delineate Dynamics of Biological Processes; 4 Advances in Hidden Markov Models for Sequence Annotation; 5 Sorting- and FFT-Based Techniques in the Discovery of Biopatterns; 6 A Survey of Seeding for Sequence Alignment; 7 The Comparison of Phylogenetic Networks: Algorithms and Complexity.…”
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Algorithms for Dummies. by Mueller, John Paul

Table of Contents: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Getting Started with Algorithms -- Chapter 1 Introducing Algorithms -- Describing Algorithms -- The right way to make toast: Defining algorithm uses -- Finding algorithms everywhere -- Using Computers to Solve Problems -- Getting the most out of modern CPUs and GPUs -- Working with special-purpose chips -- Networks: Sharing is more than caring -- Leveraging available data…”
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Algorithmic composition : a guide to composing music with Nyquist by Simoni, Mary Hope

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Nature-inspired optimization algorithms by Yang, Xin-She

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Multi-Objective Optimization in Theory and Practice II : metaheuristic algorithms. by Keller, André A.

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Swarm intelligence and bio-inspired computation : theory and applications

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Ant colony optimization by Dorigo, Marco

Table of Contents: “…Preface; Acknowledgments; 1 -- From Real to Artificial Ants; 2 -- The Ant Colony Optimization Metaheuristic; 3 -- Ant Colony Optimization Algorithms for the Traveling Salesman Problem; 4 -- Ant Colony Optimization Theory; 5 -- Ant Colony Optimization for NP-Hard Problems; 6 -- AntNet: An ACO Algorithm for Data Network Routing; 7 -- Conclusions and Prospects for the Future; Appendix: Sources of Information about the ACO Field; References; Index.…”
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Algorithmic techniques for the polymer sciences by Tice, Bradley S.

Table of Contents: “…Chapter 14: Feedback Systems for Nontraditional Medicines: A Case for the Signal Flow DiagramChapter 15: Chromatic Aspects of the Signal Flow Diagram; Chapter 16: Junction Graphs; Chapter 17: Embedded Symbol Notation Diagrams and Embedded Symbol Notation Matrix Diagrams; Chapter 18: Feedback Theory: Properties of Signal Flow Graphs; Chapter 19: An Overview of Signal Flow Graphs; Chapter 20: A Theory on Neurological Systems-Part I and Part II; Chapter 21: A Theoretical Model of Feedback in Pharmacology Using Signal Flow Diagrams; Appendix A: A New Foundation for Information.…”
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Stochastic Local Search : Foundations and Applications. by Hoos, Holger

Table of Contents: “…Empirical Analysis of SLS Algorithms; Chapter 5. Search Space Structure and SLS Performance; Part II: Applications; Chapter 6. …”
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Parallel Computing Using the Prefix Problem. by Lakshmivarahan, S.

Table of Contents: “…Chapter 3 -- Parallel Prefix Algorithms On Arrays3.1 Methods of Cyclic Elimination and Reduction; 3.2 Schwartz's Method; 3.3 An Algorithm for Fixed Parallelism; 3.4 A Balanced Binary Tree Algorithm; 3.5 Cole-Vishkin Algorithm; 3.6 A Comparison; 3.7 Exercises; 3.8 Notes and References; Chapter 4 -- Parallel Prefix Algorithms On Linked Lists; 4.1 Basic Pointer-jumping; 4.2 A Strategy for Optimal List Ranking; 4.3 Independent Set via Coloring; 4.4 Cole and Vishkin's Algorithm; 4.5 Independent Set via Randomization; 4.6 Exercises; 4.7 Notes and References; Part Three -- Algorithms For Circuit Models.…”
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Evolutionary optimization algorithms by Simon, Dan, 1960-

Table of Contents: “…Cover; Title Page; Copyright Page; SHORT TABLE OF CONTENTS; DETAILED TABLE OF CONTENTS; Acknowledgments; Acronyms; List of Algorithms; PART I INTRODUCTION TO EVOLUTIONARY OPTIMIZATION; 1 Introduction; 1.1 Terminology; 1.2 Why Another Book on Evolutionary Algorithms?…”
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Pathway modeling and algorithm research

Table of Contents: “…PATHWAY MODELING AND ALGORITHM RESEARCH; PATHWAY MODELING AND ALGORITHM RESEARCH; Contents; Preface; Biological Pathways and Their Modeling; Abstract; 1. …”
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Concurrency by Malkhi, Dahlia

Table of Contents: “…Intro -- Contents -- Preface -- Photo and Text Credits -- Introduction -- The Computer Science of Concurrency: The Early Years -- PART I. TECHNICAL PERSPECTIVES ON LAMPORT'SWORK -- 1. …”
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Providing Sound Foundations for Cryptography : On the Work of Shafi Goldwasser and Silvio Micali. by Goldreich, Oded

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A CALCULUS OF IDEAS : a MATHEMATICAL STUDY OF HUMAN THOUGHT. by Grenander, Ulf

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Data Mining Algorithms : Explained Using R. by Cichosz, Pawel

Table of Contents: “…Cover; Title Page; Copyright; Contents; Acknowledgements; Preface; Part I Preliminaries; Chapter 1 Tasks; 1.1 Introduction; 1.1.1 Knowledge; 1.1.2 Inference; 1.2 Inductive learning tasks; 1.2.1 Domain; 1.2.2 Instances; 1.2.3 Attributes; 1.2.4 Target attribute; 1.2.5 Input attributes; 1.2.6 Training set; 1.2.7 Model; 1.2.8 Performance; 1.2.9 Generalization; 1.2.10 Overfitting; 1.2.11 Algorithms; 1.2.12 Inductive learning as search; 1.3 Classification; 1.3.1 Concept; 1.3.2 Training set; 1.3.3 Model; 1.3.4 Performance; 1.3.5 Generalization; 1.3.6 Overfitting; 1.3.7 Algorithms; 1.4 Regression.…”
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