Project Management
ENGG1400
David Rey
Research Center for Integrated Transport Innovation (rCITI)
School of Civil and Environmental Engineering
UNSW Australia
Knapsack Problem
Dynamic Programming Approach
Outline
1
Knapsack Problem
2
Dynamic Programming A
ENGG1400
Name
Student ID:
Assignment #2
Please note:
Due: Wednesday, 8 October 2014 4pm (Late submission penalties apply.)
This is an individual assignment.
Please put a copy of your Assignment including all workings, in Professor Wallers
assignment drop
ENGG 1400:
Infrastructure System Optimization
Lecture #2
Prof S. Travis Waller
Email: s.waller@unsw.edu.au
Room 110, CVEN Building
Dr. David Rey
Room 105, CVEN Building
Email: d.rey@unsw.edu.au
Dr. Lauren Gardner
Email l.gardner@unsw.edu.au
Room 112, CVEN
#Week 6Model for the Minimumcost Flow Problem
#Sets
set N;
#set of nodes
set Orig;
#set of origin nodes
set Dest;
#set of destination nodes
set OD := cfw_Orig, Dest;
#set of OD pairs
set Ns := N diff cfw_Orig union Dest; #set of nodes minus origin and
#Week 6Data for the Minimumcost Flow Problem
set N := Milan Florence Rome Pescara Venice Ancona Naples Bari Bologna LaSpezia
Terni;
set A := (Milan,LaSpezia) (Milan,Venice) (LaSpzia,Bologna) (LaSpzia,Florence)
(Bologna,Venice)
(Bologna,Ancona) (Florenc
#Assignment 2Model for the Vehicle Routing Problem
#Sets
set N;
set Nc = N diff cfw_0;
set A := cfw_i in N, j in N : i<>j;
set K;
#nodes set
#customer nodes set
#arcs set
#vehicles set
#Parameters
param xAxiscfw_N;
param yAxiscfw_N;
param dcfw_(i,j) in
#Week 7Data for the Network Design Problem
set N := Honolulu Chicago SanFransisco LosAngeles Boston NewYork Atlanta London;
set A := (Honolulu,Chicago) (Honolulu,SanFransisco) (Honolulu,LosAngeles)
(Chicago,Boston) (Chicago,NewYork) (SanFransisco,Boston
# Model for VRP
#Sets
set N;
set Nc = N diff cfw_0;
set A := cfw_i in N, j in N : i<>j;
set K;
#nodes set
#customer nodes set
#arcs set
#vehicles set
#Parameters
param xAxiscfw_N;
param yAxiscfw_N;
param dcfw_(i,j) in A := sqrt(xAxis[i]  xAxis[j])*2 + (y
ENGG1400 Workshop for Week 6
NETWORK DESIGN: THE MINIMUMCOST FLOW PROBLEM
I.
Problem Description
Network design is an important infrastructure problem which can provide a solution to
several types of problems, such as:
How to supply a maximum amount of c
Transit Route Design
ENGG1400
David Rey
Research Center for Integrated Transport Innovation (rCITI)
School of Civil and Environmental Engineering
UNSW Australia
Modeling Transit Route Design
Solution Algorithm
Implementation
Outline
1
Modeling Transit Rou
SCHOOL OF CIVIL AND ENVIRONMENTAL ENGINEERING
Semester 2, 2016
ENGG 1400
Infrastructure System Optimization
COURSE DETAILS
Units of Credit
6
Contact hours
4 hours per week
Lecture
Wednesday, 12pm 3pm
Central Lecture Block 7 (KE19104)
Please refer to the
ENGG 1400:
Infrastructure System Optimization
Lecture #3
Prof S. Travis Waller
Email: s.waller@unsw.edu.au
Room 110, CVEN Building
Dr. David Rey
Room 105, CVEN Building
Email: d.rey@unsw.edu.au
Dr. Lauren Gardner
Email l.gardner@unsw.edu.au
Room 112, CVEN
#Assignment 2Model for the House Scheduling Problem
#Sets
set H;
set J;
set order within cfw_H,J,J;
#Parameters
param M >= 0;
param dcfw_H,J;
param pcfw_H,J;
set Scfw_h in H := cfw_j in J : d[h,j]=1;
#Variables
var tcfw_h in H, j in S[h] >= 0;
var xcfw_
B = 0
: x y :=
Atlanta London 350 0
Boston London 300 0
Chicago Boston 300 0
Chicago NewYork 0 0
Honolulu Chicago 300 0
Honolulu LosAngeles 350 0
Honolulu SanFransisco 350 0
LosAngeles Atlanta 350 0
LosAngeles NewYork 0 0
NewYork London 350 0
SanFransisco
ENGG1400 Exam Revision Notes Part 1:
Infrastructure Systems:
The Role Of Engineers:
Managing project teams
establishing and managing project priorities
writing project proposals
developing and maintaining client relations
maintaining project quality assur
Integer Linear Problems
Simple constraints: typically most values are given
Constraints are just inequality equations
Decision variables can only hold integer values
Facility Location Problems
Optimizing the best lo
ENGG1400
Engineering Infrastructure Systems
Week 7 Workshop
Scheduling Problem
Kasun Wijayaratna
Milad Ghasri
Scheduling Problem
A schedule is a time management tool which lists the times that
possible tasks, events, or actions are intended to take place.
Q1Continued
Part B
Part C
The optimal solution is shown below:
Q2
Part A
The following is the data file:
Part B
Part C
This data file is the same as Part B, but the following has been added on to
include capacity constraints.
Below are the optimal soluti
Part B
Part D
Same data file as above with the below section added;
The two links this truck should be assigned to are the Rome>Naples link and the
Pescara > Bari link. Therefore, the savings generated is $2639920 $2598980=
$40,940 in savings.
Part E
N
ENGG1400 WEEK 2 (Planning: Facility Location Problem)
Infrastructure Planning

Long term, strategic level decisions: things cannot easily change, spend a million
dollars to replace roads, factories, etc, theyre not very easy to pick it up and move it
els
ENGG1400
Name
Student ID:
Workshop Time/Day:
Demonstrators:
Assignment #1
Please note:
Due: Friday, 2 September 2016 5pm (Late submission penalties apply.)
This is an individual assignment.
The clarity and the presentation of the assignment will be accoun
ENGG1400
Name:
Student ID:_
Workshop Time/Day:
Demonstrators:
Assignment #2
Please note:
Due: Friday, 14 October 2016 5pm (Late submissions will not be accepted).
This is an individual assignment.
The clarity and the presentation of the assignment will be
2
Problem 1 LP Example
A) The Mathematical Formula:
Decision Variables:

x and y are real positive numbers:
x, y R
Objective Function:
 to maximise the value of the function, x + 3y:
maximise f ( x , y )=x +3 y
Constraints:
 x should be between 0 and 4