Objective, Functions, and Operations
Author : United States. Public Land Law Review Commission
Publisher :
Page : 28 pages
File Size : 14,54 MB
Release : 1966
Category : Public lands
ISBN :
Author : United States. Public Land Law Review Commission
Publisher :
Page : 28 pages
File Size : 14,54 MB
Release : 1966
Category : Public lands
ISBN :
Author : United States. Public Land Law Review Commission
Publisher :
Page : 24 pages
File Size : 47,28 MB
Release : 1966
Category : Public lands
ISBN :
Author : Tadeusz Trzaskalik
Publisher : Springer Science & Business Media
Page : 437 pages
File Size : 42,37 MB
Release : 2013-06-05
Category : Business & Economics
ISBN : 3790818127
The book is dedicated to multi-objective methods in decision making. The first part which is devoted to theoretical aspects, covers a broad range of multi-objective methods such as multiple linear programming, vector optimisation, fuzzy goal programming, data envelopment analysis, game theory, and dynamic programming. The reader who is interested in practical applications, will find in the remaining parts a variety of approaches applied in numerous fields including production planning, logistics, marketing, and finance.
Author : K V Mital
Publisher : New Age International
Page : 408 pages
File Size : 12,58 MB
Release : 1996
Category : Linear programming
ISBN : 9788122408737
The Mathematical Aspects Of Operations Research And Systems Analysis Concerned With Optimization Of Objectives Form The Subject Of This Book. In Its Revised, Updated And Enlarged Third Edition, Discussion On Linear Programming Has Been Expanded And Recast With Greater Emphasis On Duality Theory, Sensitivity Analysis, Parametric Programming, Multiobjective And Goal Programming And Formulation And Solution Of Practical Problems. Chapters On Nonlinear Programming Include Integer Programming, Kuhn-Tucker Theory, Separable And Quadratic Programming, Dynamic Programming, Geometric Programming And Direct Search And Gradient Methods. A Chapter On Theory Of Games Is Also Included. A Short Note On Karmarkars Projective Algorithm Is Given In The Appendix.The Book Keeps In View The Needs Of The Student Taking A Regular Course In Operations Research Or Mathematical Programming, And Also Of Research Scholars In Other Disciplines Who Have A Limited Objective Of Learning The Practical Aspects Of Various Optimization Methods To Solve Their Special Problems. For The Former, Illustrative Solved Examples And Unsolved Examples At The End Of Each Chapter, Small Enough To Be Solved By Hand, Would Be Of Greater Interest, While For He Latter, Summaries Of Computational Algorithms For Various Methods Which Would Help Him To Write Computer Programmes To Solve Larger Problems Would Be More Helpful. A Few Computer Programmes In Fortran Iv Have Also Been Given In The Appendix.
Author : John Tuman Westgate
Publisher :
Page : 148 pages
File Size : 11,56 MB
Release : 1980
Category : Reservoirs
ISBN :
Author : Jeffrey L. Ringuest
Publisher : Springer Science & Business Media
Page : 178 pages
File Size : 36,46 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 146153612X
Throughout the development of mathematical programming researchers have paid great attention to problems that are described by a single objective that can only be achieved subject to satisfying a set of restrictions or constraints. Recently, it has been recognized that the use of a single objective limits the applicability of In reality, many multiobjective mathematical programming models. situations exist and frequently these mUltiple objectives are in direct conflict. Research on multiobjective problems can be broken down into two broad categories: multiobjective optimization and multicriterion decision theory. Multiobjective optimization models are based on techniques such as linear programming. In general, the multiobjective optimization problem can be defined as finding a feasible alternative that yields the most preferred set of values for the objective functions. This problem differs from a single objective because subjective methods are required to determine which alternative is most preferred. A body of literature parallel to that m multiobjective optimization has been developing in the area of multicriterion decision theory. These models are based on classical decision analysis, particularly utility theory. One focus of this research has been the development and testing of procedures for estimating multiattribute utility functions that are consistent with rational decision maker behavior. A utility function provides a model of a decision maker's choice among alternatives. This literature is directly xii MULTIOBJECTIVE OPTIMIZATION applicable to multiobjective optimization and provides much needed insight into the subjective character of that problem.
Author : Ralph Allen Wurbs
Publisher :
Page : 100 pages
File Size : 45,28 MB
Release : 1991
Category : Reservoirs
ISBN :
Author : Perez C.
Publisher :
Page : 278 pages
File Size : 40,78 MB
Release : 2017-08-16
Category :
ISBN : 9781974587209
The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics. Optimization includes finding "best available" values of some objective function given a defined domain (or input), including a variety of different types of objective functions and different types of domains.Adding more than one objective to an optimization problem adds complexity. For example, to optimize a structural design, one would desire a design that is both light and rigid. When two objectives conflict, a trade-off must be created. There may be one lightest design, one stiffest design, and an infinite number of designs that are some compromise of weight and rigidity. The set of trade-off designs that cannot be improved upon according to one criterion without hurting another criterion is known as the Pareto set. The curve created plotting weight against stiffness of the best designs is known as the Pareto frontier.A design is judged to be "Pareto optimal" (equivalently, "Pareto efficient" or in the Pareto set) if it is not dominated by any other design: If it is worse than another design in some respects and no better in any respect, then it is dominated and is not Pareto optimal. The choice among "Pareto optimal" solutions to determine the "favorite solution" is delegated to the decision maker. In other words, defining the problem as multi-objective optimization signals that some information is missing: desirable objectives are given but combinations of them are not rated relative to each other. In some cases, the missing information can be derived by interactive sessions with the decision maker.Multi-objective optimization problems have been generalized further into vector optimization problems where the (partial) ordering is no longer given by the Pareto ordering.Optimization problems are often multi-modal; that is, they possess multiple good solutions. They could all be globally good or there could be a mix of globally good and locally good solutions. Obtaining all (or at least some of) the multiple solutions is the goal of a multi-modal optimizer.Classical optimization techniques due to their iterative approach do not perform satisfactorily when they are used to obtain multiple solutions, since it is not guaranteed that different solutions will be obtained even with different starting points in multiple runs of the algorithm. Evolutionary algorithms, however, are a very popular approach to obtain multiple solutions in a multi-modal optimization task.This book develops the following topics:* "Multiobjective Optimization Algorithms" * "Using fminimax with a Simulink Model" * "Signal Processing Using fgoalattain" * "Generate and Plot a Pareto Front" * "Linear Programming Algorithms" * "Maximize Long-Term Investments Using Linear Programming" * "Mixed-Integer Linear Programming Algorithms" * "Tuning Integer Linear Programming" * "Mixed-Integer Linear Programming Basics" * "Optimal Dispatch of Power Generators" * "Mixed-Integer Quadratic Programming Portfolio Optimization" * "Quadratic Programming Algorithms"* "Quadratic Minimization with Bound Constraints" * "Quadratic Minimization with Dense, Structured Hessian"* "Large Sparse Quadratic Program with Interior Point Algorithm" * "Least-Squares (Model Fitting) Algorithms" * "lsqnonlin with a Simulink Model" * "Nonlinear Least Squares With and Without Jacobian" * "Linear Least Squares with Bound Constraints" * "Optimization App with the lsqlin Solver" * "Maximize Long-Term Investments Using Linear Programming" * "Jacobian Multiply Function with Linear Least Squares" * "Nonlinear Curve Fitting with lsqcurvefit" * "Fit a Model to Complex-Valued Data" * "Systems of Equations" * "Nonlinear Equations with Analytic Jacobian" * "Nonlinear Equations with Jacobian" * "Nonlinear Equations with Jacobian Sparsity Pattern"* "Nonlinear Systems with Constraints" * "Parallel Computing for Optimization"
Author : G. Srinivasan
Publisher : PHI Learning Pvt. Ltd.
Page : 528 pages
File Size : 35,30 MB
Release : 2010-09
Category : Business & Economics
ISBN : 8120342089
The methodology used is to first expose the students to the fundamental concepts through a numerical illustration and then explain the underlying theory wherever required. The inclusion of a case study in each chapter of this second edition has made learning easier and more effective. The book introduces the readers to various models of operations research, such as the transportation model, the assignment model, the inventory model, the queueing theory and the integer programming model. The various techniques to solve OR problems faced by managers are also discussed. Separate chapters are devoted to linear programming, dynamic programming and quadratic programming which greatly help in the decision-making process.
Author : Joseph S. Martinich
Publisher : John Wiley & Sons
Page : 942 pages
File Size : 27,53 MB
Release : 2008-03-06
Category : Industrial engineering
ISBN : 9788126516094
This book explains why operations management tools are critical and how to successfully use them. Over 200 examples from real companies show how non operations professionals are using operations management concepts daily. It also introduces operations strategy early and often throughout to show how operational decisions are crucial to developing and executing a company's overall strategy.· Production Systems and Operations Management· Operations Strategy· Tours of Operations· Forecasting· Capacity Planning and Facility Location· Selecting the Process Structure and Technology· The Quality Management System· Aggregate Planning· Managing Materials with Dependent Demands· Operations and Personnel Scheduling· Project Planning and Scheduling