Download or read book Multi stage Resource Allocation Under Uncertainty written by G. Calafiore and published by . This book was released on 2003 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Project Selection Under Uncertainty written by Stylianos Kavadias and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Selection Under Uncertainty is the result of a five-year research program on the selection of projects in New Product Development (NPD). Choosing the New Product Development portfolio is of critical importance in today's business environment. The NPD portfolio has considerable strategic effect on the "middle term" success of a business. This book takes a step in developing a theory that addresses the need for quantitative prioritization criteria within the broader strategic context of the R&D portfolios. Its foundation lies in mathematical theory of resource-constrained optimization with the goal to maximize quantitative returns. The book seeks to broaden the portfolio discussion in two ways. First, simplified models - appropriate for the data-poor NPD context - are developed, which attempt to illuminate the structure of the choice problem and robust qualitative rules of thumb, rather than detailed algorithmic decision support. Such robust rules can be applied in the R&D environment of poor data availability. Second, the annual portfolio review is not the only important choice in resource allocation. In addition, the book discusses how ideas might be pre-screened as they emerge, and how projects should be prioritized once they are funded and ongoing.

Download or read book Approximate Dynamic Programming written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2007-10-05 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.

Download or read book Resource Allocation in Multi Project Environments written by Tal Ben-Zvi and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the challenges in multi-project environments is the question how to allocate resources to assure a timely completion of all planned projects. In order to increase resource utilization, managers try to allocate all available resources at the beginning of a new cycle to all planned projects.This strategy would not allow for acting on potential risks and uncertainties. Thus, current literature on multi-project planning considers buffer concepts in various forms. The problem with these strategies is their complexities and consequently their general rejection by practitioners. In this study we address the problem of resource allocation under uncertainty by developing a counter-intuitive heuristic that is simple and effective. We developed a simulation tool allowing us to test resource allocation strategies in realistic environments. Surprisingly, the results demonstrate that resource allocation strategies with less than 100% resource allocation in the planning stage enable an overall value for a project portfolio that is close to the ideal maximum. This means that managers should keep a certain percentage of resources in the planning stage idle to encounter variations in the execution phase, enabling a maximal project portfolio value.

Download or read book A mathematical model for resource allocation in emergency situations with the co operation of NGOs under uncertainty written by Deepshikha Sarma and published by Infinite Study. This book was released on with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several times people on the earth are aicted by the strike of unpredictable phenomena like a disaster. Although some non-governmental organization (NGO) involving in disaster relief operation, prepositioned some resources in disaster-prone areas, but it is not sucient for all times. Sometimes, due to the high intensive devastation, help for providing relief is requested to the other national or international aid. This research has introduced a mathematical model for humanitarian logistic considering two optimization criteria minimize the total cost and total time of the relief logistic operation with a collaboration of resource collection by the NGOs.

Download or read book Techniques for the Allocation of Resources Under Uncertainty written by Pierrick Plamondon and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vehicle Routing and Resource Allocation Under Uncertainty written by Yingtao Ren and published by LAP Lambert Academic Publishing. This book was released on 2011-09 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution.

Download or read book Optimization of Temporal Networks under Uncertainty written by Wolfram Wiesemann and published by Springer Science & Business Media. This book was released on 2012-01-05 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization problems (e.g. the task durations) are typically unknown at the time the decision problem arises. This monograph investigates solution techniques for optimization problems in temporal networks that explicitly account for this parameter uncertainty. We study several formulations, each of which requires different information about the uncertain problem parameters.

Download or read book Nonlinear Optimization for Project Scheduling and Resource Allocation Under Uncertainty written by Ali Mahmoudoff and published by . This book was released on 2006 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Optimization for Network based Resource Allocation Problems Under Uncertainty written by Lavanya Marla and published by . This book was released on 2007 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider large-scale, network-based, resource allocation problems under uncertainty, with specific focus on the class of problems referred to as multi-commodity flow problems with time-windows. These problems are at the core of many network-based resource allocation problems. Inherent data uncertainty in the problem guarantees that deterministic optimal solutions are rarely, if ever, executed. Our work examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we can generate solutions that are more robust operationally, that is, more likely to be executed or easier to repair when disrupted. The challenges are the following: approaches to achieve robustness 1) can be extremely problem-specific and not general; 2) suffer from issues of tractability; or 3) have unrealistic data requirements. We propose in this work a modeling and algorithmic framework that addresses the above challenges.

Download or read book Rough Multiple Objective Decision Making written by Jiuping Xu and published by CRC Press. This book was released on 2011-07-28 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory. Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques—and some that employ simulation-based intelligent algorithms—to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions. Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research.

Download or read book Resource Allocation Under Uncertainty written by F. H.. Trinkl and published by . This book was released on 1973 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multi stage Resource Allocation Under Asymmetric Information written by Stanley Baiman and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Topics in Model Validation and Uncertainty Quantification Volume 4 written by T. Simmermacher and published by Springer Science & Business Media. This book was released on 2012-04-23 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topics in Model Validation and Uncertainty Quantification, Volume 4, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the fourth volume of six from the Conference, brings together 19 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Robustness to Lack of Knowledge in Design Bayesian and Markov Chain Monte Carlo Methods Uncertainty Quantification Model Calibration

Download or read book Resource Allocation Under Uncertainty written by Mathias Johansson and published by . This book was released on 2004 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Resource Allocation Behavior written by Harvey J. Langholtz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the increasing necessity for information on allocating dwindling resources, resource-allocation behavior is not nearly so well understood as choice behavior (selection from two or more already defined alternatives, events, or lotteries.) Although there have been scores of books devoted to the optimal model for making resource-allocation decisions there has never been a book discussing the cognitive aspects of this behavior. This book answers the question of how people make such decisions while explaining how Linear Programming can be applied within the context of resource-allocation. It also takes the reader step-by-step into several types of problems under varying conditions, including harsh and benign environments, maximization and minimization, multi-dimensional, and cyclical problems.

Download or read book Resource Allocations in Multi stage Contests written by Aner Sela and published by . This book was released on 2021 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study best-of-k contests (k=2,3) between two players. The players have heterogeneous resource budgets that decrease within the stages proportionally to the resource allocated in the previous stages such that for each resource unit that a player allocates, he loses [alpha] (the fatigue parameter) units of resources from his budget. We show that in both contest forms, independent of the values of the fatigue parameters, each player allocates his smallest resource in the last stage. In the best-of three contest where there are different fatigue parameters for each of the two first stages, a sufficient condition that the resource allocation in the first stage is larger than in the second one is that the value of the fatigue parameter of the first stage is smaller than or equal to the value of the fatigue parameter of the second stage. We also show that in the best-of-three contest, if the fatigue parameters are sufficiently large (approaches one), both players allocate almost all their resource budgets in the first two stages such that they have no resources left for the last stage in which the winner might be decided.