CE 191: Civl and Environmental Engineering Systems Analysis

CE 191: Civl and Environmental Engineering Systems Analysis

LEC 00 : Course Introduction

Professor Scott MouraCivl & Environmental EngineeringUniversity of California, Berkeley

Fall 2013

Prof. Moura | UC Berkeley CE 191 | LEC 00 - Intro Slide 1

Why take CE 191?

Learn to abstract mathematical programs

from physical systems to “optimally” design

a civil engineered system.


Why take CE 191?

Learn to abstract mathematical programs

from physical systems to “optimally” design

a civil engineered system.


You graduated from Berkeley, you just found your dream job in your dream field, in your dream city.

One day, your boss calls you in his office, and asks you to

solve a civil and environmental engineering problem.

You spend three weeks trying to find a solution. You find « some kind of a solution, but you are not sure ».

The week after, your boss calls you again.

What do you do?

One year from today

One answer (Garey and Johnson)

[Computers and intractability, Garey and Johnson, 1979]

I can't find an efficient algorithm, I guess I'm just too dumb


Answer 1 (if you did not take CE 191)

I can't find an efficient algorithm, because no such algorithm is possible


Answer 2 (in your wildest dreams)

I can't find an efficient algorithm, but neither can all these famous people


Answer 3 (after taking CE 191)

Your boss wants the cheapest solution: -  Can you find a solution? à feasibility -  Can you find a cheaper solution? à optimality -  Can you find the cheapest solution? à uniqueness

-  Can you find a cheap solution? à suboptimal -  How cheap is your solution? à degree of suboptimality

-  Why can’t you find a cheap solution? à hardness

Problem 1: feasability, uniqueness, optimality

Your boss gives you a huge data file He does not care if your solution is cheap, as long as you can tell

him how cheap it is He wants your algorithm to find the solution of the problem in 5

minutes -  Is your algorithm fast? à polynomial time -  Is your algorithm slow? à non polynomial time

Problem 2: computational complexity

Your boss gives you a huge data file every day She is happy if you can guarantee her that on average you will give

her the optimal solution every other day in less than 5 minutes -  Does you algorithm always converge? à deterministic/random -  Does it do well on average? à expected sense

Problem 3: deterministic or not

Your boss wants to know how many trucks she needs to send to Sacramento next Friday.

Your boss wants to know how many pounds of sand she needs to

send to Sacramento next Friday. Which problem is easiest to solve for you? -  Your algorithm says: 223276.25 pounds à continuous -  Your algorithm says: 25 trucks à discrete -  Your algorithm say: 24.6 trucks à LP-rounding?

Problem 4: discrete / continuous

One of the people you supervise (from Stanford) tells you he just found the perfect model for your problem, it is very precise, but it involves the cosine of the square root of the quantity of fuel burned by your trucks.

The other person you supervise (from MIT) tells you she just found a

not so precise model, but it is proportional to the quantity of fuel burned by your trucks plus a constant.

Which one should you put in your algorithm to give the best answer

to your boss in a reasonable time? -  Tractable models à linear/affine -  Harder models à nonlinear/nonconvex

Problem 5: linear / nonlinear

Class Format

Lectures: MW 8-9am, 406 Davis Hall

Lab Section: Th 2-5pm or 5-8pm, 345 Davis Hall

Website: http://bspace.berkeley.edu

Professor Scott [email protected]

Office Hours: M,Tu,W 9-10am@ 625 Davis Hall

GSI Xiaofei [email protected]

Office Hours: Tu 10-11am, F 10-11am@ 345 Davis Hall


http://bspace.berkeley.edu

[email protected]

[email protected]

Technical Content

Optimization TopicsLinear programming (LP)

Quadratic programming (QP)

Integer programming (IP)

Dynamic programming (DP)

Nonlinear programming (NLP)

CEE TopicsWater resource management

Planning future energy supplies

Scheduling in a construction project

Investment portfolio optimization

Bicycle sharing


Textbooks

No textbooks are required,

the following is officially recommended for additional background:Civil and Environmental Systems Engineering; C. Revelle, E. Whitlatch, R.Wright; Pearson Prentice Hall, 2004.

The following textbooks are also useful resources:Convex Optimization; S. Boyd and L. Vandenberghe; Cambridge UniversityPress, 2004.Principles of Optimal Design; P. Papalambros and D. Wilde; CambridgeUniversity Press, 2000.

All textbooks have been placed on 2 hr. reserve in the library.

Lecture format:Mostly blackboard w/ some slidesSupplemental slides available online


Software

MATLAB used for lab assignments.

UCB IST License: You can request a license athttp://ist.berkeley.edu/software-central/matlab

For purchase from Mathworks for $99:http://www.mathworks.com/academia/student_version/

Computer Access: A CEE Computer Lab Account is required to use the computersin 345 Davis. Use the link below to request an account. http://www.ce.berkeley.edu/resources/computing/create_lab_account


http://ist.berkeley.edu/software-central/matlab

http://www.mathworks.com/academia/student_version/

http://www.ce.berkeley.edu/resources/computing/create_lab_account

http://www.ce.berkeley.edu/resources/computing/create_lab_account

Lab 0 - Matlab Review

Familiarize yourself with computer lab in 345 Davis

Use class website bspace.berkeley.edu

Complete survey on background

Review basic Matlab tasks

Rehearse electronic submission to bSpace


bspace.berkeley.edu

Grading

Straight scale (no curve):

Labs: 50pts - 5 lab assignments, 10pts eachMidterm: 20pts - Mon Oct 21, 8-9am

Final: 30pts - Exam Group 4: Mon Dec 16, 2013 7-10pm

A total of 100pts are possible.

Philosophy: Consistency and transparency


Policies

Late Submissions: One point is subtracted for each 24 hours submitted late (roundedup to nearest integer). Two free late days are allowed on any lab of your choice.

Regrade Policy: If you feel a problem was graded incorrectly, you may submit aregrade request to the GSI. This request MUST be submitted within one week ofreceiving the graded assignment, with a short paragraph justifying the regrade. Anyregrade request is subject to a full regrade, i.e. points may be lost.

Planned Absences: You may request to submit assignments early or late. E-mail meyour request two weeks prior to the assignment due date. Requests due to extendedholidays will not be granted. Requests due to emergencies will be handledcase-by-case.


How to Succeed

Ask questions in class

Form a study group

See instructor after class

See instructor during OH

See GSI during OH

Send us an e-mail. Use [CE 191] in subject.


Flowchart of Methods-based Courses

CE 191 Op(miza(on

E 7 Matlab Intro

CE 155 Transporta(on

Systems

CE 186 Cyber Physical

Systems

CE 268E Civil Systems & Environment

CE 271 Sensors & Signals

CE 2XX Energy Systems

& Control

CE 290I Sensors & Signals

CE 291F Control of DPS

EE 127A Op(miza(on Models & Apps

IEOR 262A/B, 263A/B, 264 Math Programming

EECS 227 Convex

Op(miza(on

EE 120, C128 Control Systems

ME C134 Control Systems

ME C23X, EE 220-‐3 Control Systems


Example 1: Barcelona Water Network

There are 67 tanks, 10 water sources, 111 valves / pumps, 88 points of water consumptionand 15 complex nodes. [Trnka, Pekar, Havlena, IFAC2011]


Example 2: Shortest Path (routing)


Example 3: Electrified Vehicle Energy Management

Optimized PHEV charging based on variableelectricity price via quadratic programming.

SUPERVISORY

CONTROLLER

M/G1

M/G2

PLANETARY

GEAR SET

BATTERY PACK

DRIVE

CYCLE

ENGINE

VEHICLE

Battery State of Charge

Acceleration

Engine

Speed

Engine

Torque

M/G1 Torque

M/G2

Torque

Vehicle

Speed

Fuel Consumption

Cost

Grid Electricity

Consumption Cost

Anode-Side Film

Growth Penalty

Optimal energy management given statisticaldriving behavior via stochastic dynamic

programming.


Documents

CE 191: Civl and Environmental Engineering Systems Analysis