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Efficient Algorithms for Strong Local Consistencies and Adaptive Techniques in Constraint Satisfaction Problems

efficient filtering algorithms for enforcing strong local consistencies. In addition, since such filtering algorithms can be too expensive to;

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Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems

DisCSP (Distributed Constraint Satisfaction Problem) is a general framework for solving distributed problems arising in Distributed;

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Constraint Satisfaction Problems

A Constraint Satisfaction Problem (CSP) consists of a set of variables, a domain of values for each variable and a set of constraints. The;

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Stochastic Local Search

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult;

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Constraint-Based Reasoning

, P. Van Hentenryck, H. Simonis, M. Dincbas * Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling;

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Complexity Dichotomies for Counting Problems

homomorphisms, constraint satisfaction problems, and Holant problems. The book assumes minimal prior knowledge of computational complexity theory;

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Vehicle Scheduling in Port Automation

five scheduling decisions. For each decision, it supplies an overview, formulates each of the decisions as constraint satisfaction and;

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Complex Scheduling

and integer programming, constraint propagation techniques, shortest path and network flow algorithms, branch-and-bound methods, local search;

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Solving Geometric Constraint Systems

Solving Geometric Constraints records and explains the formal basis for graphical analysis techniques that have been used for;

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Algorithms and Architectures

techniques, time-based techniques, techniques for reducing physical realization requirements, and applications to finite constraint problems.

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The Design of Approximation Algorithms

-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local;

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Logic-Based Methods for Optimization

optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful;

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Computational Methods for Option Pricing

of the following topics: Mathematical results and efficient algorithms for pricing American options.Modern algorithms with adaptive mesh;

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Decision Making under Constraints

techniques in other application areas. As such, the annual International Workshops on Constraint Programming and Decision Making focus on cross;

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Decision Making under Constraints

techniques in other application areas. As such, the annual International Workshops on Constraint Programming and Decision Making focus on cross;

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Classic Computer Science Problems in Java

algorithms * Constraint-satisfaction problems * Graph algorithms * K-means clustering For intermediate Java programmers;

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A Brief Introduction to Continuous Evolutionary Optimization

function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive;

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Ant Colony Optimization and Constraint Programming

author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint;

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Self-Adaptive Heuristics For Evolutionary Computation

mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the;

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Constraint Processing

Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and reduce the realm of possibilities to;

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Adaptive Stochastic Optimization Techniques with Applications

Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on;

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Introduction to Propositional Satisfiability

Propositional logic allows for description and then solving of a significant class of constraint satisfaction problems, namely those that;

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Planning, Scheduling and Constraint Satisfaction

planning, scheduling, constraint satisfaction, mixed-initiative planning and scheduling, temporal reasoning, knowledge representation, formal;

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Interval Methods for Solving Nonlinear Constraint Satisfaction, Optimization and Similar Problems

This book highlights recent research on interval methods for solving nonlinear constraint satisfaction, optimization and similar problems;

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Numerica

of Numerica is based on a combination of traditional numerical methods such as interval and local methods, and constraint satisfaction techniques;

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Algorithms and Data Structures in Action

techniques for improving priority queues, efficient caching, clustering data, and more. Each example is fully illustrated with graphics, language;

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Compressed Sensing in Li-Fi and Wi-Fi Networks

detection, greedy algorithms, and the use of graphical models. The book can be used as a comprehensive manual for teaching and research in courses;

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