Edward J. Anderson – författare
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4 produkter
4 produkter
Häftad, Engelska, 2003
507 kr
Skickas inom 3-6 vardagar
Inbunden, Engelska, 2013
833 kr
Skickas inom 5-8 vardagar
A comprehensive and accessible introduction to modern quantitative risk management.The business world is rife with risk and uncertainty, and risk management is a vitally important topic for managers. The best way to achieve a clear understanding of risk is to use quantitative tools and probability models. Written for students, this book has a quantitative emphasis but is accessible to those without a strong mathematical background.Business Risk Management: Models and Analysis Discusses novel modern approaches to risk managementIntroduces advanced topics in an accessible mannerIncludes motivating worked examples and exercises (including selected solutions)Is written with the student in mind, and does not assume advanced mathematicsIs suitable for self-study by the manager who wishes to better understand this important field. Aimed at postgraduate students, this book is also suitable for senior undergraduates, MBA students, and all those who have a general interest in business risk.
Häftad, Engelska, 2022
235 kr
Skickas inom 5-8 vardagar
The plain language guide to getting things running smoothly in the world of business Operations management is all about efficiency, and Operations Management For Dummies is all about efficiently teaching you what you need to know about this business hot topic. This book tracks typical operations management MBA courses, and it will help you un-muddle concepts like process mapping, bottlenecks, Lean Production, and supply chain management. Learn to step into a business, see what needs improving, and plug in the latest tools and ideas to shape things up in any industry. This latest edition covers, you guessed it, digital transformation. Technology is completely upending operations management, and Dummies walks you through the latest, so you can stay at the front of the pack. Other new stuff inside: supply chain traceability, ethical sourcing and carbon footprint, business resiliency, and modularizing the supply chain. It’s all here! Optimize operations and increase revenue with strategies and ideas that make businesses run better and cheaper Get easy-to-understand explanations of complex topics and theories in operations management Learn how operations management is affected by digital transformation and sustainability concerns Evaluate, design, improve, and scale all sorts of processes, regardless of business size or area of operation Businesses can't operate successfully without effective operations and supply management. That makes Operations Management For Dummies a must—for MBA students and business professionals alike.
Häftad, Engelska, 1985
1 105 kr
Skickas inom 10-15 vardagar
Infinite programming may be defined as the study of mathematical programming problems in which the number of variables and the number of constraints are both possibly infinite. Many optimization problems in engineering, operations research, and economics have natural formul- ions as infinite programs. For example, the problem of Chebyshev approximation can be posed as a linear program with an infinite number of constraints. Formally, given continuous functions f,gl,g2, ••• ,gn on the interval [a,b], we can find the linear combination of the functions gl,g2, ... ,gn which is the best uniform approximation to f by choosing real numbers a,xl,x2, •.. ,x to n minimize a t€ [a,b]. This is an example of a semi-infinite program; the number of variables is finite and the number of constraints is infinite. An example of an infinite program in which the number of constraints and the number of variables are both infinite, is the well-known continuous linear program which can be formulated as follows. T minimize ~ c(t)Tx(t)dt t b(t) , subject to Bx(t) + fo Kx(s)ds x(t) .. 0, t € [0, T] • If x is regarded as a member of some infinite-dimensional vector space of functions, then this problem is a linear program posed over that space. Observe that if the constraint equations are differentiated, then this problem takes the form of a linear optimal control problem with state IV variable inequality constraints.