Download or read book Strategic allocation of resources using linear programming model with parametric analysis in MATLAB and Excel Solver written by Dinesh Gupta and published by diplom.de. This book was released on 2014-05-01 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the late 1940s, linear programming models have been used for many different purposes. Airline companies apply these models to optimize their use of planes and staff. NASA has been using them for years to optimize their use of limited resources. Oil companies use them to optimize their refinery operations. Small and medium-sized businesses use linear programming to solve a huge variety of problems, often involving resource allocation. In my study, a typical product-mix problem in a manufacturing system producing two products (each product consists of two sub-assemblies) is solved for ist optimal solution through the use of the latest versions of MATLAB having the command simlp, which is very much like linprog. As analysts, we try to find a good enough solution for the decision maker to make a final decision. Our attempt is to give the mathematical description of the product-mix optimization problem and bring the problem into a form ready to call MATLAB’s simlp command. The objective of this study is to find the best product mix that maximizes profit. The graph obtained using MATLAB commands, give the shaded area enclosed by the constraints called the feasible region, which is the set of points satisfying all the constraints. To find the optimal solution we look at the lines of equal profit to find the corner of the feasible region which yield the highest profit. This corner can be found out at the farthest line of equal profit, which still touches the feasible region. The most critical part is the sensitivity analysis, using Excel Solver, and Parametric Analysis, using computer software, which allows us to study the effect on optimal solution due to discrete and continuous change in parameters of the LP model including to identify bottlenecks. We have examined other options like product outsourcing, one-time cost, cross training of one operator, manufacturing of hypothetical third product on under-utilized machines and optimal sequencing of jobs on machines.

Download or read book Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis written by Dinesh Gupta and published by GRIN Verlag. This book was released on 2014-03-31 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2013 in the subject Engineering - Industrial Engineering and Management, grade: Good, LMU Munich (Dr. B R Ambedkar National Institute of Technology, Jalandhar), course: Industrial Engg., language: English, abstract: Since the late 1940s, linear programming models have been used for many different purposes. Airline companies apply these models to optimize their use of planes and staff. NASA has been using them for many years to optimize their use of limited resources. Oil companies use them to optimize their refinery operations. Small and medium-sized businesses use linear programming to solve a huge variety of problems, often involving resource allocation. In my study, a typical product-mix problem in a manufacturing system producing two products (each product consists of two sub-assemblies) is solved for its optimal solution through the use of the latest versions of MATLAB having the command simlp, which is very much like linprog. As analysts, we try to find a good enough solution for the decision maker to make a final decision. Our attempt is to give the mathematical description of the product-mix optimization problem and bring the problem into a form ready to call MATLAB’s simlp command. The objective of this paper is to find the best product mix that maximizes profit. The graph obtained using MATLAB commands, give the shaded area enclosed by the constraints called the feasible region, which is the set of points satisfying all the constraints. To find the optimal solution we look at the lines of equal profit to find the corner of the feasible region which yield the highest profit. This corner can be found out at the farthest line of equal profit which still touches the feasible region. The most critical part is the sensitivity analysis using Excel Solver and Parametric Analysis using computer software which allows us to study the effect on optimal solution due to discrete and continuous change in parameters of the LP model including to identify bottlenecks. We have examined other options like product outsourcing, one-time cost, cross training of one operator, manufacturing of hypothetical third product on under-utilized machines and optimal sequencing of jobs on machines.

Download or read book Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis in MATLAB and Excel Solver written by Dinesh Gupta and published by Anchor Academic Publishing (aap_verlag). This book was released on 2014-05-27 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the late 1940s, linear programming models have been used for many different purposes. Airline companies apply these models to optimize their use of planes and staff. NASA has been using them for many years to optimize their use of limited resources. Oil companies use them to optimize their refinery operations. Small and medium-sized businesses use linear programming to solve a huge variety of problems, often involving resource allocation. In my study, a typical product-mix problem in a manufacturing system producing two products (each product consists of two sub-assemblies) is solved for its optimal solution through the use of the latest versions of MATLAB having the command simlp, which is very much like linprog. As analysts, we try to find a good enough solution for the decision maker to make a final decision. Our attempt is to give the mathematical description of the product-mix optimization problem and bring the problem into a form ready to call MATLAB’s simlp command. The objective of this study is to find the best product mix that maximizes profit. The graph obtained using MATLAB commands, give the shaded area enclosed by the constraints called the feasible region, which is the set of points satisfying all the constraints. To find the optimal solution we look at the lines of equal profit to find the corner of the feasible region which yield the highest profit. This corner can be found out at the farthest line of equal profit, which still touches the feasible region. The most critical part is the sensitivity analysis, using Excel Solver, and Parametric Analysis, using computer software, which allows us to study the effect on optimal solution due to discrete and continuous change in parameters of the LP model including to identify bottlenecks. We have examined other options like product outsourcing, one-time cost, cross training of one operator, manufacturing of hypothetical third product on under-utilized machines and optimal sequencing of jobs on machines.

Download or read book Linear Programming and Resource Allocation Modeling written by Michael J. Panik and published by John Wiley & Sons. This book was released on 2018-11-06 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Guides in the application of linear programming to firm decision making, with the goal of giving decision-makers a better understanding of methods at their disposal Useful as a main resource or as a supplement in an economics or management science course, this comprehensive book addresses the deficiencies of other texts when it comes to covering linear programming theory—especially where data envelopment analysis (DEA) is concerned—and provides the foundation for the development of DEA. Linear Programming and Resource Allocation Modeling begins by introducing primal and dual problems via an optimum product mix problem, and reviews the rudiments of vector and matrix operations. It then goes on to cover: the canonical and standard forms of a linear programming problem; the computational aspects of linear programming; variations of the standard simplex theme; duality theory; single- and multiple- process production functions; sensitivity analysis of the optimal solution; structural changes; and parametric programming. The primal and dual problems are then reformulated and re-examined in the context of Lagrangian saddle points, and a host of duality and complementary slackness theorems are offered. The book also covers primal and dual quadratic programs, the complementary pivot method, primal and dual linear fractional functional programs, and (matrix) game theory solutions via linear programming, and data envelopment analysis (DEA). This book: Appeals to those wishing to solve linear optimization problems in areas such as economics, business administration and management, agriculture and energy, strategic planning, public decision making, and health care Fills the need for a linear programming applications component in a management science or economics course Provides a complete treatment of linear programming as applied to activity selection and usage Contains many detailed example problems as well as textual and graphical explanations Linear Programming and Resource Allocation Modeling is an excellent resource for professionals looking to solve linear optimization problems, and advanced undergraduate to beginning graduate level management science or economics students.

Download or read book Modeling and Solving Linear Programming with R written by Jose M. Sallan and published by OmniaScience. This book was released on 2015-09-09 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear programming is one of the most extensively used techniques in the toolbox of quantitative methods of optimization. One of the reasons of the popularity of linear programming is that it allows to model a large variety of situations with a simple framework. Furthermore, a linear program is relatively easy to solve. The simplex method allows to solve most linear programs efficiently, and the Karmarkar interior-point method allows a more efficient solving of some kinds of linear programming. The power of linear programming is greatly enhanced when came the opportunity of solving integer and mixed integer linear programming. In these models all or some of the decision variables are integers, respectively. In this book we provide a brief introduction to linear programming, together with a set of exercises that introduce some applications of linear programming. We will also provide an introduction to solve linear programming in R. For each problem a possible solution through linear programming is introduced, together with the code to solve it in R and its numerical solution.

Download or read book Optimization Models for Resource Allocation Under Perturbation written by Dongxue Bridgeman and published by . This book was released on 2013 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Models for Resource allocation are investing in how to make the best use of available but limited resources in order to achieve the best results. In strategic planning, resource allocation is a plan for using available resources, especially in the near future, to achieve the goals of the future. It is a process of allocating resources during the entire planning horizon and among the various units. Resource allocation plans can be decided by using mathematical programming. In this dissertation, the research has been focused on how to allocate resources in the uncertain environment. The mathematical programming formulations for the resource allocation model under severe uncertainty will be studied. In particular, we will focus on solving the stability issues of the traditional probabilistic model. We propose an approach consisting of solving a sequence of convex robust optimization models with unknown-but-bounded random variables along with the stochastic programming to pursue the allocation performance for the expected overall objective value. Our theoretical results show that the proposed approach can always obtain an equivalent or a better expected revenue with the corresponding allocation, while significantly reducing the risk under perturbations. Although this method requires solving two convex mathematical programming models, both models are solved within a timely manner thanks to their convex model instances and with effective, and less, computationally demanding algorithms. With the increasing threats from public health emergencies, such as earthquakes, tornados, pandemic flus, or terrorist attacks, high attention has been paid to the public health response to a pandemic from federal to national level, together with local health departments, and the health-care community. Various organizations cooperate with each other to strengthen the preparedness for the pandemic and disastrous emergencies, thus to improve the public health. The Strategic National Stockpile (SNS) is maintained by the Centers for Disease Control and Prevention (CDC) and the U.S. Department of Health and Human Services (DHHS) for the United States in the event of a shortage of local medical resources or other unanticipated supply problems. The SNS is the United States' national repository of antibiotics, vaccines, chemical antidotes, antitoxins, and other critical medical equipment and supplies. It has the capability to supplement or re-supply local health authorities with necessary materials for relief action within the response time in as little as 12 hours. The pilot study is done with the support of Kentucky SNS to determine the capacity allocation plan for each county in order to maximize the health benefit under various uncertainties, which can never be accurately estimated. We thereby employ a heuristic method named "resource reservation" to suggest the resource allocation plan for Kentucky SNS.

Download or read book Planning with Linear Programming written by E Alaphia Wright and published by CRC Press. This book was released on 1996-01-01 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work deals with the background to linear programming (LP) using a largely non-mathematical treatment. It covers several planning cases and the LP-tools suite of programs. Copies of the programs on a distribution disk are included with the book.

Download or read book Optimization Methods for Resource Allocation written by Richard Cottle and published by . This book was released on 1974 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Probabilistic Information in Solving Resource Allocation Problems for a Decentralized Firm written by James R. Freeland and published by . This book was released on 1978 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Linear and Integer Programming with Excel Examples written by Fernando A. Boeira and published by . This book was released on 2015-03-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Maximizing subject to constraints, that is, making use of scarce resources, is the central theme of economics. But students of economics are often taught the mathematics of optimization as a branch of mathematics, and its economics application follow separately.This book is aimed for undergraduate students in economics, engineering, operations research, or other disciplines dealing with a branch of optimization theory: linear and integer programming. It supports a variety of teaching and learning and integrates the use of spreadsheets with instructions for Microsoft Excel.

Download or read book Optimization Methods in Finance written by Gerard Cornuejols and published by Cambridge University Press. This book was released on 2006-12-21 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.

Download or read book Resource Allocation Using Linear Programming written by Tanya Merritt and published by . This book was released on 1994 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Postoptimal Analyses Parametric Programming and Related Topics written by Tomáš Gál and published by McGraw-Hill Companies. This book was released on 1979 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mixed integer Optimization Approaches to Resource Allocation Problems with Applications in Healthcare Asset Management and Epidemics written by Emmanuel Des Bordes and published by . This book was released on 2015 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we study mixed-integer programming (MIP) approaches to solve resource allocation problems with applications in healthcare asset management and epidemics. In particular, we study (i) valid inequalities for solving large-scale one-dimensional zero-one (0–1) knapsack problems (KPs), (ii) healthcare asset-replacement problems that involve several styles and types of magnetic resonance imaging (MRI) machines, and (iii) epidemics involving the Ebola virus disease (EVD) under resource constraints. Using recursive solutions of the dynamic programming (DP), we present valid inequalities that can be added to the original 0–1 KP as cutting planes (CP) to tighten and improve the model formulation for facilitating solution methods. Extensive computational experiments show that our inequalities yield competitive results. Operating assets generally suffer from deterioration, which results in high operation and maintenance (O&M) cost and decreased salvage value, while technologies allow newer machines to operate more efficiently at a lower cost. Therefore, we study the multiple style and type parallel asset-replacement problem (MST-PRES), which determines an optimal policy for keeping or replacing a group of assets that operate in parallel under a limited budget. Results show that the proposed MIP model provides valuable insights and strategies for decision-makers and government entities on the capital asset management. Epidemic diseases, which are occurring more frequently, are a major health and economic problem for mankind. This section begins with a review of epidemiological disease models that have been used to study transmission dynamics of Ebola and their estimated key parameters from existing data set in order to explain important patterns by which it spreads to make significant public healthcare decisions. Following the review of Ebola, we develop a mixed-integer optimization of epidemic model to address the efficient allocation of epidemic resources and to assess the impact of traveling within Guinea, Liberia, and Sierra Leone for control of the 2014 Ebola outbreak. We conclude by presenting effective combinations of future intervention strategies and policy recommendation for controlling the EVD epidemics.

Download or read book Optimization Modelling written by Ruhul Amin Sarker and published by CRC Press. This book was released on 2007-10-15 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although a useful and important tool, the potential of mathematical modelling for decision making is often neglected. Considered an art by many and weird science by some, modelling is not as widely appreciated in problem solving and decision making as perhaps it should be. And although many operations research, management science, and optimization

Download or read book The Allocation of Resources by Linear Programming written by Robert Gary Bland and published by . This book was released on 1981 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crystal-like structures in many geometrical dimensions can help to solve problems in planning and management. A new algorithm has set upper limits on the complexity of such problems.

Download or read book Solution of Large Scale Allocation Problems with Partially Observable Outcomes written by Kirk A. Yost and published by . This book was released on 1998-09-01 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop methods for optimally solving problems that require allocating scarce resources among activities that either gather information on a set of objects or take actions to change their status. Also, the information we gather on the outcomes of the actions we take may be erroneous. The latter situation is called partial observability, and methodology available prior to this dissertation is combinatorially intractable for problems with more than one object. We use two previously-uncombined methods - linear programming (LP) and partially observable Markov decision processes (POMDPs) - to construct a decomposition procedure to solve the resulting large-scale allocation problem with partially observable outcomes. We show theoretically that this procedure is both optimal and finite; in addition, we develop improvements to the procedure that reduce runtimes on test problems by 95%. We demonstrate the procedure on a small targeting problem with a known analytical solution, as well as a large- scale military example concerned with allocating aircraft sorties, weapons, and bomb-damage assessment sensors to targets. Finally, we develop analytical bounds on the expected objective function values of a related allocation problem with more stringent resource constraints, and present a simulation-based approach to estimate the distributions of the outcomes for that model.