Linear Programming and its Applications Homework II
LP Formulations
Solve all the problems.
Problem 1: Radio manufacturing (Chvatal)
An electronics company has a contract to deliver 20,000 radios within the next four weeks. The
client is willing to pay $2
Formulating and solving linear programs
1
Solving linear programs
Problem 1: Solving 2-variable LP by graphical method
Solve each of the problems below by the sketching the constraint set and optimizing the objective
function over the feasible set.
1.
Max
Baris Aksanli
Department of Computer Science and Engineering
UCSD
System Energy Eciency Lab
seelab.ucsd.edu
Models of Computation
State Machine Models
Petri nets
Communicating Processes
Kahn processes, Communicating
Linear Programming and its Applications Homework I
Problem 1: Solving by graphical method
Solve the following linear programs using the graphical method.
1.
Maximize
9x1 + 15x2
x1 2x2 1
subject to
2x1 x2 1
x1 , x2 0
2.
Minimize
2x1 + 3x2
x1 3x2 6
subject
Linear Programming and its Applications Homework I
Problem 1: Solving by graphical method
Solve the following linear programs using the graphical method.
1.
Maximize
9x1 + 15x2
x1 2x2 1
subject to
2x1 x2 1
x1 , x2 0
2.
Minimize
2x1 + 3x2
x1 3x2 6
subject
CSE 190, Fall 2015: Assignment 2
Instructions
This is an open-ended assignment in which you are expected to write a detailed report documenting your
results. Please submit your solution in class or electronically to Long Jin (longjin@cs.ucsd.edu), on or b
CSE 190, Fall 2015: Assignment 1
Instructions
In this assignment you will build recommender systems to make predictions related to reviews of Books on
Amazon.
Solutions will be graded on Kaggle (see below), with the competition closing at midnight, Novemb
CSE 190, Fall 2015: Homework 4
Instructions
Please submit your solution at the beginning of the Monday week 9 lecture (November 23) or outside
of CSE 4102 beforehand. Please complete homework individually.
Download the 50,000 beer reviews data from the co
CSE 190, Fall 2015: Homework 3
Please submit your solution at the beginning of the Monday week 7 lecture (Nov 9) or outside of CSE
4102 beforehand. Please complete homework individually.
These homework exercises are intended to help you get started on pot
CSE 190, Spring 2015: Homework 2
Instructions
Please submit your solution at the beginning of the Monday week 5 lecture (October 26) or outside
of CSE 4102 beforehand. Please complete homework individually.
You will need the following les:
50,000 beer rev
CSE 190, Fall 2015: Homework 1
Instructions
Please submit your solution at the beginning of the week 3 lecture (October 12) or outside of CSE
4102 beforehand. Please complete homework individually.
You will need the following les:
50,000 beer reviews : ht
import gzip
from collections import defaultdict
def readGz(f):
for l in gzip.open(f):
yield eval(l)
# Helpfulness baseline: similar to the above. Compute the global average
helpfulness rate, and the average helpfulness rate for each user
allHelpful = []
u
Linear Programming and its Applications Homework III
Applications
For each of the problems below, formulate the linear program, code the linear program in AMPL,
and solve it using the package. Your output must include the formulation of the linear program
Linear Programming and its Applications Homework II
LP Formulations
Solve all the problems.
Problem 1: Radio manufacturing (Chvatal)
An electronics company has a contract to deliver 20,000 radios within the next four weeks. The
client is willing to pay $2
Baris Aksanli
Department of Computer Science and Engineering
UCSD
System Energy Eciency Lab
seelab.ucsd.edu
ES Design
Hardware components
Hardware
Verification and Validation
CSE190 Embedded Computing
2
Models, Languages and To
Baris Aksanli
Department of Computer Science and Engineering
UCSD
System Energy Eciency Lab
seelab.ucsd.edu
Models of Computation
State Machine Models
Petri nets
Communicating Processes
Kahn processes, Communicating
CSE 190G Spring 2016: Project
The goal of this project is to develop an energy-efficient EDF(Earliest Deadline First) scheduler, which
handles multiple workloads controlling sensors running on Raspberry PI 2 (RPi2). During the course of
the project, you w
CSE190G Embedded Computing Spring 2016 Homework 1
1 Petri Nets (25 pts)
Assume you have a Petri Net N, with P places, T transitions and F flows:
P = cfw_P1, P2, P3, P4
T = cfw_T1, T2, T3
F = cfw_(P1, T1), (P2, T1), (P2, T2), (P3, T3), (P4, T3), (T1, P3),
Simplex Method
Problem 1: Canonical form
Convert each of the linear programming problems below to canonical form. A linear program is
said to be in canonical form if it has the following format:
Maximize
cT x
subject to
Ax b
x0
where c and x are n-dimensi
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953
9?
WV
1. What Is It, and What For?
Linear pmg‘ramming. suri‘wisingly, is; not directly related to (tmnpu’tm‘ pm»
gramniiiig. The term was intrmlucecl in, the 1950s; when computers WTTO few
and irriomly mp secrets, and the word programming; was a
Linear Programming Solution Types
This note presents examples of each type of Linear Programming solution. Note that all examples
here are for maximization, but minimization problems have analogous solution types.
Example 1: Bounded Region with a Unique S
LP Dualty
Problem 1: Writing the dual linear program
Write the dual to the following linear program.
Maximize
subject to
x1 + x2
2x1 + 3x2 3
x1 + 3x2 5
x1 , x2 0
Problem 2: Writing the dual linear program
Write the dual to the following linear program.
x1
Applications of Linear Programming
1
Applications
Problem 1: Points on a circle (Nivasch)
We are given a nite set S R2 of points in the plane, and somebody claims that these points lie
appoximately on a circle. How can this be veried ? Here is one possibl
Applications of Linear Programming
1
Applications
Problem 1: Points on a circle (Nivasch)
We are given a nite set S R2 of points in the plane, and somebody claims that these points lie
appoximately on a circle. How can this be veried ? Here is one possibl
Platform Thinking
Sneha (TA)
CSE 190
Case Studies
Ubers Dynamic Pricing
Increase cost based on
Wait times
# unfulfilled requests
Incentive to increase supply
Intentionally decrease demand
Maintain quality
Lead to 70-80% increase in supply
Whats with Gr
import gzip
from collections import defaultdict
def readGz(f):
for l in gzip.open(f):
yield eval(l)
# Helpfulness baseline: similar to the above. Compute the global average
helpfulness rate, and the average helpfulness rate for each user
allHelpful = []
u
Discrete and Continuous Optimization Sample Mid-term I
Maximum Points: 30
Time: 75 minutes
Date: October 25, 2016
Solve ALL FOUR problems. In each case, present your work clearly. Provide proofs or
arguments as needed.
Problem 1: Infeasible LP
Show that t
Discrete and Continuous Optimization Homework I
Problem 1: Solving by graphical method
Solve the following linear programs using the graphical method.
1.
Maximize
9x1 + 15x2
x1 2x2 1
subject to
2x1 x2 1
x1 , x2 0
2.
Minimize
2x1 + 3x2
x1 3x2 6
subject to