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Paul Pfeiffer - Topics in Applied Probability

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Paul Pfeiffer Topics in Applied Probability

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This collection includes some m-files for problems supplementary to Pfeiffer: Applied Probability. In addition, the text file collection New Prob mfiles contains both the user defined programs for that work and a collection of mfiles for specific problems with properly formatted data which can be entered into the workspace by calling the appropriate file. These m-files come from a variety of sources ( e.g., exams or problem sets, hence the odd names) and may be useful for examples and exercises.

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Topics in Applied Probability

Collection edited by: Paul Pfeiffer

Content authors: Daniel Williamson and Paul Pfeiffer

Online:

This selection and arrangement of content as a collection is copyrighted by Paul Pfeiffer .

It is licensed under the Creative Commons Attribution License: http://creativecommons.org/licenses/by/3.0/

Collection structure revised: 2009/09/04

For copyright and attribution information for the modules contained in this collection, see the "" section at the end of the collection.

Preface

Topics in Applied Probability is meant to supplement the collection Applied Probability with examples, further problems, and m-files. This collection is not meant to stand alone but rather serve as a miscellany of further content not included in the original collection. Topics discussed in this collection include Martingale Sequences and Markov Procedures as well as a few others. In addition, the collection of m-files contains both the user-defined programs and a collection of m-files for specific problems with properly formatted data.

MATLAB Files

These files can be entered into MATLAB by calling the appropriate file. These m-files come from a variety of sources ( e.g., exams or problem sets, hence the odd names) and may be useful for examples and exercises. In order to allow for easy access to the helpful m-files, a supplementary link has been placed in the upper right side of each module in the "Topics in Applied Probability" collection. Selecting this link will launch the download of a zip document containing a suite of m-files. Unzipping this file and saving its contents to your local system will allow for easy and reliable access when working with MATLAB.

Cost with Price Breaks

Let D be the demand random variable. Suppose there is

A flat fee of C for Da 1
A cost of c1 per unit for a 1 < Da 2
A cost of c2 per unit for a 2 < Da 3
A cost of c3 per unit for a 3 < D

Then (see figure)

(1)
Topics in Applied Probability - image 1
Note

Since Topics in Applied Probability - image 2 at t = ai , we could as well have Topics in Applied Probability - image 3 .

Special Case. If D is Poisson () , we may obtain an exact solution for E [ g ( D )] by using thefact that and 2 - photo 4 and

(2)
As an alternate approach we approximate D by an appropriate number of values - photo 5

As an alternate approach, we approximate D by an appropriate number of values.

Exercise 1. Example ()

A residential College is planning a camping trip over Spring Recess.The number D of persons planning to go is assumed to be Poisson (15). Arrangementsfor transportation and food have been made as follows:

If D 4 , a minimal flat fee of $450 will be charged.
If 4 < D 19 , the additional charge is $100 for each person more than 4 (butless than 20).
If 19 < D , the charge is $80 for each person more than 19.
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