SyllabusIntroductionSyllabus IntroductionMath 364: Principles of Optimization, Lecture 1Haijun [email protected] of MathematicsWashington State UniversitySpring 2012Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 1 / 11Syllabus IntroductionSyllabusCourse page: www.math.wsu.edu/math/faculty/lih/364.htmlIntroduction to Mathematical Programming by W.L.Winston and M. Venkataramanan, 4th ed.We will cover material from chapters 2-6 (linearprogramming, simplex method, sensitivity analysis,duality), and 11 (game theory).Homework assignments: approx. 7, assigned andcollected in class (30%).Project: The modeling software AMPL will be used. Youmay work in pairs on this assignment and turn in one paperper partnership (10%).Exam 1: tentatively scheduled for February 23, in class(30%).Exam 2: April 19, in class (30%).Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 2 / 11Syllabus IntroductionSyllabusCourse page: www.math.wsu.edu/math/faculty/lih/364.htmlIntroduction to Mathematical Programming by W.L.Winston and M. Venkataramanan, 4th ed.We will cover material from chapters 2-6 (linearprogramming, simplex method, sensitivity analysis,duality), and 11 (game theory).Homework assignments: approx. 7, assigned andcollected in class (30%).Project: The modeling software AMPL will be used. Youmay work in pairs on this assignment and turn in one paperper partnership (10%).Exam 1: tentatively scheduled for February 23, in class(30%).Exam 2: April 19, in class (30%).Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 2 / 11Syllabus IntroductionSyllabusCourse page: www.math.wsu.edu/math/faculty/lih/364.htmlIntroduction to Mathematical Programming by W.L.Winston and M. Venkataramanan, 4th ed.We will cover material from chapters 2-6 (linearprogramming, simplex method, sensitivity analysis,duality), and 11 (game theory).Homework assignments: approx. 7, assigned andcollected in class (30%).Project: The modeling software AMPL will be used. Youmay work in pairs on this assignment and turn in one paperper partnership (10%).Exam 1: tentatively scheduled for February 23, in class(30%).Exam 2: April 19, in class (30%).Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 2 / 11Syllabus IntroductionGrading scale: A (94–100), A– (90–93), B+ (88–89), B(84–87), B– (80–83), C+ (78–79), C (74–77), C– (70–73), D+(68–69), D (60–67), F (≤ 59).Homework is to be turned in at the beginning of class onthe designated due date. No late homework is accepted.Solution keys (for assignments & exams) will be posted onthe web page.No compensation for missed exams will be consideredunless prior approved arrangements have been made.Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 3 / 11Syllabus IntroductionGrading scale: A (94–100), A– (90–93), B+ (88–89), B(84–87), B– (80–83), C+ (78–79), C (74–77), C– (70–73), D+(68–69), D (60–67), F (≤ 59).Homework is to be turned in at the beginning of class onthe designated due date. No late homework is accepted.Solution keys (for assignments & exams) will be posted onthe web page.No compensation for missed exams will be consideredunless prior approved arrangements have been made.Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 3 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 4 / 11Syllabus IntroductionIn Math 364, we extend the case of optimization for linearfunctions to higher dimensions.linear.png (PNG Image, 293x289 pixels) http://people.richland.edu/james/lecture/m116/systems/linear.png1 of 1 11/24/2011 9:29 PMFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 5 / 11Syllabus IntroductionA Motivating ExampleA student has five hours to kill one day, and he has to options:get tutored or partying. He has some limited budget: $48, say.Cost: tutoring = $8/hr, partying = $16/hr.Reward (utility): tutoring = 2/hr, partying = 3/hr.Decision to make: How many hours to party, and how manyhours to get tutored, as to maximize the total reward?Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 6 / 11Syllabus IntroductionA Motivating ExampleA student has five hours to kill one day, and he has to options:get tutored or partying. He has some limited budget: $48, say.Cost: tutoring = $8/hr, partying = $16/hr.Reward (utility): tutoring = 2/hr, partying = 3/hr.Decision to make: How many hours to party, and how manyhours to get tutored, as to maximize the total reward?Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 6 / 11Syllabus IntroductionA Motivating ExampleA student has five hours to kill one day, and he has to options:get tutored or partying. He has some limited budget: $48, say.Cost: tutoring = $8/hr, partying = $16/hr.Reward (utility): tutoring = 2/hr, partying = 3/hr.Decision to make: How many hours to party, and how manyhours to get tutored, as to maximize the total reward?Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 6 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 7 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 8 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 9 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 10 / 11Syllabus IntroductionFigure:Haijun Li Math 364: Principles of Optimization, Lecture 1 Spring 2012 11 /