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Stochastic Algorithms: Foundations and Applications

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Cover of 'Stochastic Algorithms: Foundations and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Systems of Containers and Enumeration Problems
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    Chapter 2 Some Heuristic Analysis of Local Search Algorithms for SAT Problems
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    Chapter 3 Clustering in Stochastic Asynchronous Algorithms for Distributed Simulations
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    Chapter 4 On Construction of the Set of Irreducible Partial Covers
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    Chapter 5 Recent Advances in Multiobjective Optimization
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    Chapter 6 Polynomial Time Checking for Generation of Finite Distributions of Rational Probabilities
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    Chapter 7 FPL Analysis for Adaptive Bandits
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    Chapter 8 On Improved Least Flexibility First Heuristics Superior for Packing and Stock Cutting Problems
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    Chapter 9 Evolutionary Testing Techniques
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    Chapter 10 Optimal Fuzzy CLOS Guidance Law Design Using Ant Colony Optimization
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    Chapter 11 On Some Bounds on the Size of Branching Programs (A Survey)
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    Chapter 12 Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization
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    Chapter 13 Self-replication, Evolvability and Asynchronicity in Stochastic Worlds
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    Chapter 14 New Computation Paradigm for Modular Exponentiation Using a Graph Model
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    Chapter 15 Dynamic Facility Location with Stochastic Demands
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    Chapter 16 The Complexity of Classical and Quantum Branching Programs: A Communication Complexity Approach
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    Chapter 17 On the Properties of Asymptotic Probability for Random Boolean Expression Values in Binary Bases
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    Chapter 18 Solving a Dynamic Cell Formation Problem with Machine Cost and Alternative Process Plan by Memetic Algorithms
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    Chapter 19 Eco-Grammar Systems as Models for Parallel Evolutionary Algorithms
Attention for Chapter 19: Eco-Grammar Systems as Models for Parallel Evolutionary Algorithms
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