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Optimization Approaches for Solving String Selection Problems

Optimization Approaches for Solving String Selection Problems provides an overview of optimization methods for a wide class of genomics;

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Metaheuristics for String Problems in Bio-Informatics

sequences are constantly arising and researchers are highly in need of efficient optimization techniques for solving them. One obstacle for;

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Data Correcting Approaches in Combinatorial Optimization

Data Correcting Approaches in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable;

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Ant Colony Optimization and Constraint Programming

declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including;

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Advances in Learning Automata and Intelligent Optimization

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world;

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Variational Analysis and Set Optimization

duality statements are given. New numerical methods for efficiently solving set optimization problems are provided. Moreover, applications;

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Variational Analysis and Set Optimization

duality statements are given. New numerical methods for efficiently solving set optimization problems are provided. Moreover, applications;

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A Derivative-free Two Level Random Search Method for Unconstrained Optimization

literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a;

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Optimization Techniques for Solving Complex Problems

.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world;

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A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results;

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Partitional Clustering via Nonsmooth Optimization

implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering;

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Partitional Clustering via Nonsmooth Optimization

implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering;

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Evolutionary Algorithms

operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are;

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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

Two approaches are known for solving large-scale unconstrained optimization problems-the limited-memory quasi-Newton method (truncated;

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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

Two approaches are known for solving large-scale unconstrained optimization problems-the limited-memory quasi-Newton method (truncated;

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Optimization Modelling

approaches. The book demonstrates the use of optimization packages through the solution of various mathematical models and provides an interpretation;

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Business Optimization Using Mathematical Programming

integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with;

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Optimization in Solving Elliptic Problems

- the optimization of numerical algorithms for solving elliptic problems. It presents detailed discussions of how asymptotically optimal;

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Optimization of Power System Problems

problems, the traditional methods are not suitable approaches for solving large-scale power system operation dilemmas. The integration;

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Facility Layout

book also covers important practical considerations for solving the formulations. The breadth of approaches presented help the reader to learn;

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Facility Layout

book also covers important practical considerations for solving the formulations. The breadth of approaches presented help the reader to learn;

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Evolutionary Multi-Criterion Optimization

selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.;

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Brits Speak Out

their theoretical analysis and introduces models for solving nonlinear programming problems and combinatorial optimization problems.;

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Bilevel Programming Problems: Theory, Algorithms and Applications to Energy Networks

in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas;

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Healthcare Staff Scheduling: Emerging Fuzzy Optimization Approaches

for more personalized healthcare, further research into multi-criteria solution approaches to staff scheduling is imperative. Healthcare;

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Healthcare Staff Scheduling: Emerging Fuzzy Optimization Approaches

for more personalized healthcare, further research into multi-criteria solution approaches to staff scheduling is imperative. Healthcare;

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Modeling and Optimization: Theory and Applications

algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and address the application of deterministic;

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