OperationsResearch.com

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As optimization techniques have developed, a gap has arisen between the people devising the methods and the people who actually need to use them. Research into methods is necessarily long-term and located usually in academic establishments; whereas the application of an optimization technique, normally in an industrial environment, has to be justified financially in the short term. The gap is probably inevitable; but there is no need for textbooks to reflect it. Tea… More >>

Optimization in Industry: Optimization techniques

Tommy and Angelica have to divide a dozen cookies between themselves. Tommy’s parents have given Angelica the responsibility of choosing how to split them. The catch: if Tommy doesn’t like the offer, he can reject it and leave both children with nothing. How do they rationally work through their situation? This video also serves as a soft introduction to forward introduction–note that we must guess what sort of offers the first player will make and then check to see how the second player will respond.

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Introduces recent advances and developments in iterative methods for solving Markovian queing and manufacturing problems, presenting future directions for research as well. Features numerous exercises and fully-worked examples. For students, practitioners and researchers in applied mathematics, scientific computing and operational research. DLC: Queing Theory. … More >>

Iterative Methods for Queuing and Manufacturing Systems

Researchers have found a new tool to help marine biologists better grasp the processes under the sea: They have created mathematical models to unveil the bacterial community dynamics behind afflictions that bleach and kill coral.

View full post on ScienceDaily: Mathematical Modeling News

a new mathematical model describes the fracture process for materials such as glass, polymers, concrete, ceramics, metals, rocks, and even certain geological fractures. The simulation model is powerful enough to predict and describe crack patterns in structures ranging in size from the microscopic to others as large as certain geological faults.

View full post on ScienceDaily: Mathematical Modeling News

Business performance management consists of a set of management and analytic processes, supported by technology, that enable businesses to define strategic goals and then measure and manage performance against those goals. BPM processes include financial and operational planning, consolidation and reporting, business modeling, analysis, and monitoring of key performance indicators linked to strategy. BPM involves consolidation of data from various sources, querying, and analysis of the data, and putting the results into practice.

Difference between business intelligence and business performance management.

• BPM (Business performance management) contains the concept of a control or feedback loop that helps guide the business towards its goals.
• BI (Business intelligence) may provide the analytics to help the business set those goals and to monitor progress towards them.

BPM enhances processes by creating better feedback loops. Continuous and real-time reviews can help to identify and eliminate problems before they grow. BPM’s forecasting abilities help companies take corrective action in time to meet earning projections. Forecasting is characterized by a high degree of predictability which is put into good use to answer what-if scenarios.

BPM can help in risk analysis and in predicting outcomes of merger and acquisition scenarios and in planning to overcome potential problems.

Methodologies

Methodologies for implementing BPM.

• Six sigma
• Balanced scorecard
• Activity based costing (ABC)
• Total Quality management (TQM)
• Integrated strategic measurement

Areas where BPM is used

1. customer-related numbers:
   1. new customers acquired
   2. status of existing customers
   3. attrition of customers (including breakup by reason for attrition)
2. Turnover generated by segments of the customers – possibly using demographic filters
3. Outstanding balances held by segments of customers and terms of payment – possibly using demographic filters
4. Collection of bad debts within customer relationships
5. Demographic analysis of individuals (potential customers) applying to become customers, and the levels of approval, rejections and pending numbers
6. Delinquency analysis of customers behind on payments
7. Profitability of customers by demographic segments and segmentation of customers by profitability.
8. Campaign management
9. Real-time dashboard on key operational metrics
   1. Overall equipment effectiveness
10. Click stream analysis on a website
11. key product portfolio trackers
12. Marketing channel analysis
13. Sales data analysis by product segments
14. Call center metrics

 Strategic Solutions used for effective implementation of BPM

• OLAP — online analytical processing,   
• Score card, dash board and data visualization
• Data warehouses
• Document warehouses
• Text mining
• DM — data mining
• BPO — business performance optimization
• EIS — executive information systems
• DSS — decision support systems
• MIS — management information systems

 Challenges when implementing a BPM program

• Goal-alignment queries: one must first determine the short- and medium-term purpose of the program. What strategic goal(s) of the organization will be addressed by the program? What organizational mission/vision does it relate to? A hypothesis needs to be crafted that details how this initiative will eventually improve results / performance.
• Baseline queries: current information-gathering competency needs assessing. Do we have the capability to monitor important sources of information? What data is being collected and how is it being stored? What are the statistical parameters of this data, e.g., how much random variation does it contain? Is this being measured?
• Cost and risk queries: someone should estimate the financial consequences of a new BI initiative. It is necessary to assess the cost of the present operations and the increase in costs associated with the BPM initiative. What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
• Customer and stakeholder queries: determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers / stakeholders will benefit directly from this initiative? Who will benefit indirectly? What quantitative / qualitative benefits follow? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customer benefits be monitored? What about employees, shareholders, and distribution channel members?
• Metrics-related queries: information requirements need operationalization into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
• Measurement methodology-related queries: one should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will data be collected? Are there any industry standards for this? Is this the best way to do the measurements? How do we know that?
• Results-related queries: someone should monitor the BPM program to ensure that it meets objectives. Adjustments in the program may be necessary. The program should be tested for accuracy, reliability, and validity. How can it be demonstrated that the BI initiative, and not something else, contributed to a change in results? How much of the change was probably random?

Product Description
Integer programming (discrete optimization) is best used for solving problems involving discrete, whole elements. Using integer variables, one can model logical requirements, fixed costs, sequencing and scheduling requirements, and many other problem aspects. Whether it’s taught in OR graduate programs or in math or computer science programs; in courses called “Integer Programming,” “Combinatorial Optimization,” “Combinatorial Optimization and Integer Programming”… More >>

Logic and Integer Programming

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In real-world problems related to finance, business, and management, mathematicians and economists frequently encounter optimization problems. In this classic book, George Dantzig looks at a wealth of examples and develops linear programming methods for their solutions. He begins by introducing the basic theory of linear inequalities and describes the powerful simplex method used to solve them. Treatments of the price concept, the transportation problem, and matrix … More >>

Linear Programming and Extensions

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The methodological development of integer programming has grown by leaps and bounds in the past four decades, with its main focus on linear integer programming. However, the past few years have also witnessed certain promising theoretical and methodological achievements in nonlinear integer programming. These recent developments have produced applications of nonlinear (mixed) integer programming across a variety of various areas of scientific computing, engineering,… More >>

Nonlinear Integer Programming

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Deals with the estimation of natural resources using a Monte Carlo methodology. Includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Discusses the geostatistical simulation techniques in such a specific way. … More >>

Geostatistical Simulation: Models and Algorithms

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David Skinner shares the wealth of his experience and expertise about decision making in a clear, practical way. The additional material and insight recorded in the Third Edition reflect his own growth as a decision analysis consultant, Rice faculty member, CEO of a large consulting firm, and maturing of his thinking. This book is an excellent resource for managers, technical professionals, and decision analysts, regardless of your experience level with decision ana… More >>

Introduction to Decision Analysis

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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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An algorithm that calculates the sensitivity to the systematic error of the fitted parameters of a least-squares regression model, with respect to the known parameters, i… More >>

Analysis of the sensitivity to the systematic error in least-squares regression models

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This is the first textbook that fully explains the neuro-dynamic programming/reinforcement learning methodology, which is a recent breakthrough in the practical application of neural networks and dynamic programming to complex problems of planning, optimal decision making, and intelligent control. Neuro-dynamic programming uses neural network approximations to overcome the “curse of dimensionality” and the “curse of modeling” that have been the bottlenecks to the… More >>

Neuro-Dynamic Programming

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The coupling of models from different physical domains and the efficient and reliable simulation of multidisciplinary problems in engineering applications are important topics for various fields of engineering, in simulation technology and in the development and analysis of numerical solvers. The volume presents advanced modelling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and … More >>

Simulation Techniques for Applied Dynamics

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Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction,… More >>

Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine

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Special features of the book 1. A very comprehensive and accessible approach in the presentation of the material. 2. A variety of solved examples to illustrate the theoretical results. 3. A large number of unsolved exercises for the students are given for practice at the end of each section. 4. Solution to each unsolved examples are given at the end of each exercise. Readership: This book is written to meet the requirements of Engineering/Science and Manageme… More >>

Optimization Techniques in Operation Research

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This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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The vehicle scheduling problem, arising in public transport bus companies, addresses the task of assigning buses to cover a given set of timetabled trip… More >>

A time-space network based exact optimization model for multi-depot bus scheduling

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Biologically inspired optimization methods constitute a rapidly expanding field of research, with new applications appearing on an almost daily basis, as optimization problems of ever-increasing complexity appear in science and technology. This book provides a general introduction to such optimization methods, along with descriptions of the biological systems upon which the methods are based. The book also covers classical optimization methods, making it possible fo… More >>

Biologically Inspired Optimization Methods: An Introduction

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To perform computer simulation successfully, two rather different sets of skills are required. One of these relates to programming: a simulation program should do what its author intends and do it efficiently. The other is concerned with the collection and analysis of data: statistical tools have to be used in order to obtain with a minimum of effort, accurate and reliable estimates for the desired performance measures. Dr Mitrani covers both of these aspects of the… More >>

Simulation Techniques for Discrete Event Systems

Operational Research (OR) is a signpost career for students studying maths or anyone with a wider interest in problem solving. This video is an introduction to OR, gives a flavour of its wide-ranging applications and aims to demonstrate that OR is an interested and varied career. Its just one of the resources available at www.learnaboutor.co.uk