LEC 00 : Course Introduction

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1 CE 191: Civl and Environmental Engineering Systems Analysis LEC 00 : Course Introduction Professor Scott Moura Civl & Environmental Engineering University of California, Berkeley Fall 2013 Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 1

2 Why take CE 191? Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 2

3 Why take CE 191? Learn to abstract mathematical programs from physical systems to optimally design a civil engineered system. Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 2

4 One year from today 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?

5 One answer (Garey and Johnson) [Computers and intractability, Garey and Johnson, 1979]

6 Answer 1 (if you did not take CE 191) I can't find an efficient algorithm, I guess I'm just too dumb [Computers and intractability, Garey and Johnson, 1979]

7 Answer 2 (in your wildest dreams) I can't find an efficient algorithm, because no such algorithm is possible [Computers and intractability, Garey and Johnson, 1979]

8 Answer 3 (after taking CE 191) I can't find an efficient algorithm, but neither can all these famous people [Computers and intractability, Garey and Johnson, 1979]

9 Problem 1: feasability, uniqueness, optimality 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

10 Problem 2: computational complexity 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

11 Problem 3: deterministic or not 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

12 Problem 4: discrete / continuous 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: pounds à continuous - Your algorithm says: 25 trucks à discrete - Your algorithm say: 24.6 trucks à LP-rounding?

13 Problem 5: linear / nonlinear 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

14 Class Format Lectures: MW 8-9am, 406 Davis Hall Lab Section: Th 2-5pm or 5-8pm, 345 Davis Hall Website: Professor Scott Moura Office Hours: M,Tu,W 625 Davis Hall GSI Xiaofei Hu xiaofei@berkeley.edu Office Hours: Tu 10-11am, F 345 Davis Hall Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 3

15 Technical Content Optimization Topics Linear programming (LP) Quadratic programming (QP) Integer programming (IP) Dynamic programming (DP) Nonlinear programming (NLP) CEE Topics Water resource management Planning future energy supplies Scheduling in a construction project Investment portfolio optimization Bicycle sharing Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 4

16 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, The following textbooks are also useful resources: Convex Optimization; S. Boyd and L. Vandenberghe; Cambridge University Press, Principles of Optimal Design; P. Papalambros and D. Wilde; Cambridge University Press, All textbooks have been placed on 2 hr. reserve in the library. Lecture format: Mostly blackboard w/ some slides Supplemental slides available online Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 5

17 Software MATLAB used for lab assignments. UCB IST License: You can request a license at For purchase from Mathworks for $99: Computer Access: A CEE Computer Lab Account is required to use the computers in 345 Davis. Use the link below to request an account. berkeley.edu/resources/computing/create_lab_account Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 6

18 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 Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 7

19 Grading Straight scale (no curve): Labs: 50pts - 5 lab assignments, 10pts each Midterm: 20pts - Mon Oct 21, 8-9am Final: 30pts - Exam Group 4: Mon Dec 16, pm A total of 100pts are possible. Philosophy: Consistency and transparency Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 8

20 Policies Late Submissions: One point is subtracted for each 24 hours submitted late (rounded up 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 a regrade request to the GSI. This request MUST be submitted within one week of receiving the graded assignment, with a short paragraph justifying the regrade. Any regrade request is subject to a full regrade, i.e. points may be lost. Planned Absences: You may request to submit assignments early or late. me your request two weeks prior to the assignment due date. Requests due to extended holidays will not be granted. Requests due to emergencies will be handled case-by-case. Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 9

21 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 . Use [CE 191] in subject. Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 10

Flowchart of Methods-based Courses E 7 Matlab Intro CE 155

Models & Apps EE 120, C128 Control Systems CE 186 Cyber Physical

Environment CE 271 Sensors & Signals CE 2XX Energy Systems &

262A/B, 263A/B, 264 Math Programming ME C23X, EE 220-3 Control

22 Flowchart of Methods-based Courses E 7 Matlab Intro CE 155 Transporta(on Systems CE 191 Op(miza(on EE 127A Op(miza(on Models & Apps EE 120, C128 Control Systems CE 186 Cyber Physical Systems ME C134 Control Systems CE 268E Civil Systems & Environment CE 271 Sensors & Signals CE 2XX Energy Systems & Control CE 290I Sensors & Signals CE 291F Control of DPS IEOR 262A/B, 263A/B, 264 Math Programming ME C23X, EE Control Systems EECS 227 Convex Op(miza(on Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 11

23 Example 1: Barcelona Water Network There are 67 tanks, 10 water sources, 111 valves / pumps, 88 points of water consumption and 15 complex nodes. [Trnka, Pekar, Havlena, IFAC2011] Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 12

24 Example 2: Shortest Path (routing) Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 13

variable electricity price via quadratic programming.

25 Example 3: Electrified Vehicle Energy Management SUPERVISORY CONTROLLER M/G1 Torque M/G2 Torque Vehicle Speed Engine Speed ENGINE Engine Torque PLANETARY GEAR SET M/G1 M/G2 Acceleration DRIVE CYCLE Battery State of Charge BATTERY PACK VEHICLE Optimized PHEV charging based on variable electricity price via quadratic programming. Fuel Consumption Cost Grid Electricity Consumption Cost Anode-Side Film Growth Penalty Optimal energy management given statistical driving behavior via stochastic dynamic programming. Prof. Moura UC Berkeley CE 191 LEC 00 - Intro Slide 14

EE/AA 578: Convex Optimization

EE/AA 578: Convex Optimization Instructor: Maryam Fazel University of Washington Fall 2016 1. Introduction EE/AA 578, Univ of Washington, Fall 2016 course logistics mathematical optimization least-squares;