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Book Strategic allocation of resources using linear programming model with parametric analysis  in MATLAB and Excel Solver

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.

Book Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis

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.

Book Optimization Models for Resource Allocation Under Perturbation

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.

Book Solution of Large Scale Allocation Problems with Partially Observable Outcomes

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.

Book Optimization Methods for Resource Allocation

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:

Book Optimal Five Year Planning Using Mixed Integer Linear Programming  Three Models Implemented for Naval Air Test Center

Download or read book Optimal Five Year Planning Using Mixed Integer Linear Programming Three Models Implemented for Naval Air Test Center written by Christos Efthimios Mavrikas and published by . This book was released on 1979 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of Linear Programming (LP) models in the resource allocation process of organizations with workload partitioned in discrete projects was examined by developing two integer and one mixed-integer, large-scale LP models. These models have been implemented to seek optimal five-year project plans for Naval-Air-Test-Center (NATC), involving a workforce numbered in hundreds and a budget of millions of dollars. In allocating resources, the optimal solution is the solution which yields the 'best' value, or the most desirous return to the organization; this return can also be called the solution benefit. Solutions should also be feasible in terms of the limitations on the availability of the resources by location and by time. MODEL-1 and MODEL-2 use a static workforce distribution and MODEL-3 allows limited reallocation of personnel to improve the solution; when reallocation is ordered, both reduction in labor efficiency and a penalty in the project benefit are introduced by MODEL-3. All three models have been implemented successfully using real data from NATC.

Book Operations Research

Download or read book Operations Research written by Charles M. Harvey and published by North-Holland. This book was released on 1979 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear optimization. Formulation of linear optimization models. The simplex algorithm. The simplex algorithm: further topics. Further topics in linear optimization. Postoptimal analysis and duality theory. Transportation models and related types of models. Multiperiod models for production and inventory; Integer programming models. Decision analysis. Probability: the quantification of uncertainty. Decision making under uncertainty. Value and utility: the quantification of preferences. Statistical decision theory.

Book Resource Allocation Using Linear Programming

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:

Book Optimal Five Year Planning Using Mixed Integer Linear Programming  Three Models Implemented for Naval Air Test Center

Download or read book Optimal Five Year Planning Using Mixed Integer Linear Programming Three Models Implemented for Naval Air Test Center written by and published by . This book was released on 1979 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of Linear Programming (LP) models in the resource allocation process of organizations with workload partitioned in discrete projects was examined by developing two integer and one mixed-integer, large-scale LP models. These models have been implemented to seek optimal five-year project plans for Naval-Air-Test-Center (NATC), involving a workforce numbered in hundreds and a budget of millions of dollars. In allocating resources, the optimal solution is the solution which yields the 'best' value, or the most desirous return to the organization; this return can also be called the solution benefit. Solutions should also be feasible in terms of the limitations on the availability of the resources by location and by time. MODEL-1 and MODEL-2 use a static workforce distribution and MODEL-3 allows limited reallocation of personnel to improve the solution; when reallocation is ordered, both reduction in labor efficiency and a penalty in the project benefit are introduced by MODEL-3. All three models have been implemented successfully using real data from NATC.

Book Mixed integer Optimization Approaches to Resource Allocation Problems with Applications in Healthcare Asset Management and Epidemics

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.

Book Linear Programming  An Application to Total Force Structure Active and Reserve

Download or read book Linear Programming An Application to Total Force Structure Active and Reserve written by Francis A. I Bowers (Jr) and published by . This book was released on 1972 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of the study is to take a quantitative approach in deriving adequate and accurate cost and effectiveness measures for Active Army and Reserve component forces; and secondly, in applying three methods of linear programming to alternative mixes of these forces in order to structure the total force requirement to meet the national security objectives in 1975. The analytical process of systems analysis and the fixed-budget approach are used to develop a linear programming model to solve the resource allocation problem. Geometric, simplex, and matrix methods are applied to alternative linear programming models using a new measure of effectiveness-deployability. (Modified author abstract).

Book Optimization Methods in Finance

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.

Book Optimization Modelling

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

Book Multiobjective Linear Programming

Download or read book Multiobjective Linear Programming written by Dinh The Luc and published by Springer. This book was released on 2015-07-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineering or operations research involve conflicting criteria and therefore it is more convenient to formulate them as multicriteria optimization models, the solution concepts and methods of which cannot be treated using traditional mathematical programming approaches.

Book Optimization in Practice with MATLAB

Download or read book Optimization in Practice with MATLAB written by Achille Messac and published by Cambridge University Press. This book was released on 2015-03-19 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is designed for students and industry practitioners for a first course in optimization integrating MATLAB® software.

Book Discrete Choice Methods with Simulation

Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.