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Stochastic Optimization with Simulation Based Optimization

. In comparison with existing simulation based optimization methods, the proposed framework leads to better solutions especially for problems with high;

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Stochastic Simulation Optimization

comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation;

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Stochastic Process Optimization using Aspen Plus (R)

in several case studies. Key Features: * The book links simulation and optimization through numerical analyses and stochastic;

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Stochastic Process Optimization using Aspen Plus (R)

. Key Features: * The book links simulation and optimization through numerical analyses and stochastic optimization techniques * Includes;

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Stochastic Simulation Optimization For Discrete Event Systems

millions or even billions of events with many variables and constraints, modeling these stochastic simulations has long been a hard nut to crack;

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Introduction To Stochastic Search And Optimization

real-world problems. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction;

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Simulation-Based Optimization

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and;

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Black Box Simulation Optimization

-making problems. Response Surface Methodology (RSM) is a black box simulation optimization method with its origin in the 1950's. Being a black;

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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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Portfolio Optimization with Different Information Flow

Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic;

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Stochastic Global Optimization

and its applications in chemical engineering. Stochastic Global Optimization - a monograph with contributions by leading researchers in the;

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Intelligent Control

approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic;

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Natural Computing for Simulation-Based Optimization and Beyond

and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review;

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Stochastic Optimization Methods: Applications in Engineering and Operations Research

problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under;

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New Optimization Algorithms and their Applications

New Optimization Algorithms and Applications: Atom-Based, Ecosystem-Based and Economics-Based presents the development of three new;

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Research on Ship Design and Optimization Based on Simulation-Based Design (SBD) Technique

Ship optimization design is critical to the preliminary design of a ship. With the rapid development of computer technology, the simulation;

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Optimization in Engineering Sciences

stochastic optimization, as well as methods and tools for computer-aided decision-making and simulation for decision-making.;

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Stochastic Hydrology and Its Use in Water Resources Systems Simulation and Optimization

for incorporating hydrological randomness and uncertainty into the simulation and optimization of water resources systems.;

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Optimization Under Stochastic Uncertainty

This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease;

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Optimization Under Stochastic Uncertainty

This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease;

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Monte-carlo Methods and Stochastic Processes

focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear;

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Monte-Carlo Methods and Stochastic Processes

focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear;

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Stochastic Global Optimization Methods and Applications to Chemical, Biochemical, Pharmaceutical and Environmental Processes

mainly focuses on stochastic, evolutionary, and artificial intelligence optimization algorithms with a special emphasis on their design, analysis;

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Designing Engineering Structures using Stochastic Optimization Methods

designed. Many new engineering design applications based on stochastic optimization techniques in automotive, energy, military, naval;

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Numerical Simulation-based Design

This book focuses on numerical simulation-based design theory and methods in mechanical engineering. The simulation-based design;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming. The book;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming. The book;

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