IOE 310 Lecture Notes - Lecture 3: Supply Chain, Minimax, Linear Programming

• School: U of M
• Department: Industrial And Operations Engineering
• Course: IOE 310
• Professor: Amy Cohn

Document Summary

Course objective: decision making in complex systems, use math models= real world decision making problems and use algorithms to find optimal and feasible solutions. About finding best solution without having to look at them all. Modeling of optimization problems (defined by: decisions (variables, rules (constraints, goal/metrics (objective function, parameters = input data that is given to you. Diet problem: choose what foods to eat to minimize cost subject to satisfying minimum requirements of protein and taste, maximum limits on calories and fat. Traveling salesman problem: choose sequence of cities to visit, minimizing distance, subject to visiting every city exactly once. There can be more than one optimal solution x+y+z=5 min x. Each variable represent question that can be answered w # Types of variables: continuous, continuous non negative, integer, binary. St ax = b a11x1+a12x2 +a1nxn=b1, am1x1+am2x2 . amnxn=bn. Repeat expression with substitutions xi>=0 i=13 = x1>=0, x2>=0, x3>=0. Add new variable to measure slack in constraint (non negative) +s.