Simulation Based Optimization

Simulation Based Optimization
Author: Abhijit Gosavi
Publsiher: Springer
Total Pages: 508
Release: 2014-10-30
Genre: Business & Economics
ISBN: 9781489974914

Download Simulation Based Optimization Book in PDF, Epub and Kindle

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Handbook of Simulation Optimization

Handbook of Simulation Optimization
Author: Michael C Fu
Publsiher: Springer
Total Pages: 387
Release: 2014-11-13
Genre: Business & Economics
ISBN: 9781493913848

Download Handbook of Simulation Optimization Book in PDF, Epub and Kindle

The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.

Research on Ship Design and Optimization Based on Simulation Based Design SBD Technique

Research on Ship Design and Optimization Based on Simulation Based Design  SBD  Technique
Author: Bao-Ji Zhang,Sheng-Long Zhang
Publsiher: Springer
Total Pages: 234
Release: 2018-05-30
Genre: Technology & Engineering
ISBN: 9789811084232

Download Research on Ship Design and Optimization Based on Simulation Based Design SBD Technique Book in PDF, Epub and Kindle

Ship optimization design is critical to the preliminary design of a ship. With the rapid development of computer technology, the simulation-based design (SBD) technique has been introduced into the field of ship design. Typical SBD consists of three parts: geometric reconstruction; CFD numerical simulation; and optimization. In the context of ship design, these are used to alter the shape of the ship, evaluate the objective function and to assess the hull form space respectively. As such, the SBD technique opens up new opportunities and paves the way for a new method for optimal ship design. This book discusses the problem of optimizing ship’s hulls, highlighting the key technologies of ship optimization design and presenting a series of hull-form optimization platforms. It includes several improved approaches and novel ideas with significant potential in this field

Simulation and Optimization in Finance

Simulation and Optimization in Finance
Author: Dessislava A. Pachamanova,Frank J. Fabozzi
Publsiher: John Wiley & Sons
Total Pages: 786
Release: 2010-09-23
Genre: Business & Economics
ISBN: 9780470882122

Download Simulation and Optimization in Finance Book in PDF, Epub and Kindle

An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.

Simulation and Optimization in Process Engineering

Simulation and Optimization in Process Engineering
Author: Michael Bortz,Norbert Asprion
Publsiher: Elsevier
Total Pages: 428
Release: 2022-04-16
Genre: Technology & Engineering
ISBN: 9780323850445

Download Simulation and Optimization in Process Engineering Book in PDF, Epub and Kindle

Simulation and Optimization in Process Engineering: The Benefit of Mathematical Methods in Applications of the Process Industry brings together examples where the successful transfer of progress made in mathematical simulation and optimization has led to innovations in an industrial context that created substantial benefit. Containing introductory accounts on scientific progress in the most relevant topics of process engineering (substance properties, simulation, optimization, optimal control and real time optimization), the examples included illustrate how such scientific progress has been transferred to innovations that delivered a measurable impact, covering details of the methods used, and more. With each chapter bringing together expertise from academia and industry, this book is the first of its kind, providing demonstratable insights. Recent mathematical methods are transformed into industrially relevant innovations. Covers recent progress in mathematical simulation and optimization in a process engineering context with chapters written by experts from both academia and industry Provides insight into challenges in industry aiming for a digitized world.

Natural Computing for Simulation Based Optimization and Beyond

Natural Computing for Simulation Based Optimization and Beyond
Author: Silja Meyer-Nieberg,Nadiia Leopold,Tobias Uhlig
Publsiher: Springer
Total Pages: 60
Release: 2019-07-26
Genre: Business & Economics
ISBN: 9783030262150

Download Natural Computing for Simulation Based Optimization and Beyond Book in PDF, Epub and Kindle

This SpringerBrief bridges the gap between the areas of simulation studies on the one hand, and optimization with natural computing on the other. Since natural computing methods have been applied with great success in several application areas, a review concerning potential benefits and pitfalls for simulation studies is merited. The brief presents such an overview and combines it with an introduction to natural computing and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review which covers both the methodological background and recent application cases. The brief is intended to serve two purposes: First, it can be used to gain more information concerning natural computing, its major dialects, and their usage for simulation studies. It also covers the areas of multi-objective optimization and neuroevolution. While the latter is only seldom mentioned in connection with simulation studies, it is a powerful potential technique. Second, the reader is provided with an overview of several areas of simulation-based optimization which range from logistic problems to engineering tasks. Additionally, the brief focuses on the usage of surrogate and meta-models. The brief presents recent application examples.

Optimization of Stochastic Models

Optimization of Stochastic Models
Author: Georg Ch. Pflug
Publsiher: Springer Science & Business Media
Total Pages: 384
Release: 2012-12-06
Genre: Business & Economics
ISBN: 9781461314493

Download Optimization of Stochastic Models Book in PDF, Epub and Kindle

Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

Antenna Design by Simulation Driven Optimization

Antenna Design by Simulation Driven Optimization
Author: Slawomir Koziel,Stanislav Ogurtsov
Publsiher: Springer Science & Business Media
Total Pages: 141
Release: 2014-02-12
Genre: Mathematics
ISBN: 9783319043678

Download Antenna Design by Simulation Driven Optimization Book in PDF, Epub and Kindle

This Brief reviews a number of techniques exploiting the surrogate-based optimization concept and variable-fidelity EM simulations for efficient optimization of antenna structures. The introduction of each method is illustrated with examples of antenna design. The authors demonstrate the ways in which practitioners can obtain an optimized antenna design at the computational cost corresponding to a few high-fidelity EM simulations of the antenna structure. There is also a discussion of the selection of antenna model fidelity and its influence on performance of the surrogate-based design process. This volume is suitable for electrical engineers in academia as well as industry, antenna designers and engineers dealing with computationally-expensive design problems.