Lab #2
Methodology
We have identified and will focus on three aspects of this project, which are data analysis,
modeling and optimization, and GUI development.
1.
Data analysis: This involves finding probability distributions of call arrivals and service
1. VBA was also used to record the correlation between job-type, in view of creating
optimized skillsets
a. A skillset matrix was created, with the entry in row I, column j represents the
number of different zip codes where both jobs I and j occurred.
b.
Lab #5
Statistical Analysis
Our first step in analyzing the data was to get a preliminary visual representation using Excel.
From this visual we derived some basic assumptions and characteristics regarding the data which
is list below:
a.1) Higher call ar
Optimization Model 2
Determine the Upper Bound: Scheduling Solution
Program Code Available with Complete Notation in Appendix
The purpose of this program is to determine the upper bound of employees to schedule over a set
of results from Model 2. The prog
Optimization Model 3
Sub combine()
'-'-'-'-'IE 372 - UPPER BOUND FINDER
'Based on the Results of Multiple Service Call Sets, Finds Upper Bound Such That Implemented Results Would
'Satisfy Needs of Each Service Call Set
'-'-'-'-
Statistical Analysis
Process:
1. Preliminary visual representation using Excel
a. Objective: derive some basic assumptions and characteristics regarding the data:
b. Results:
b.i. Higher call arrival volume Monday thru Friday, lower on weekends
b.ii. Non-
Lab #4
Now that we have formatted all the service calls such that they correspond to the time intervals,
we can now populate the parameter d. The information for the parameter d is stored in a
collection of matrices where each matrix corresponds to a base
Lab #3
In order to populate the elements of parameter d from a set of service calls, a VBA program was
written to automate the formatting. First, the program assigns the proper base station to each
service call based on the results from Model 1. Model 1 a
Approach
Given the sheer enormity of the project, we have decided to develop the
optimization solution in two phases, involving separate but intertwined models. With this
approach, the team can divide and conquer; the models can be developed independent o
Lab #6
Graphical User Interface
Approach: We approached the problem with the principle of making the GUI easy to use, and
decided Visual Basic was the best way to do so. The GUI consists of a series of form, with the
ability to navigate both backwards and
Lab #1
Executive Summary
Using the rational unified process, we developed the optimal solution by creating two separate
intertwined models. Before we started on our models we performed a data analysis in order to
find distributions of the variables and ot
Approach: We approached the problem with the principle of making the GUI easy to use, and
decided Visual Basic was the best way to do so. The GUI consists of a series of form, with the
ability to navigate both backwards and forwards between the forms; thi