uses the python program 1- Sketching the optimal level set of the objective function and find optimal value 1) using ploting objective function contours and also 2) checking vertex points. maximize subject to (Hint: optimal value = 42) 2x + 3y -3x + y =<2 4x + 2y = < 44 4x- y =< 20 _x +2y =<14 x, y >=0

uses the python program 1- Sketching the optimal level set of the objective function and find optimal value 1) using ploting objective function contours and also 2) checking vertex points. maximize subject to (Hint: optimal value = 42) 2x + 3y -3x + y =<2 4x + 2y = < 44 4x- y =< 20 _x +2y =<14 x, y >=0

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Similar questions

Use Dynamic programming to solve "0/1 Knapsack Problem" Unbounded Knapsack Problem (many copies for the item) The W = 7 (max weight) Items # of available copies Item weight Item benefit TELE 1 3 1 11 2 2 2 10 3 4 3 30
Q4) By using Graphical Method to determine the optimal value of X1 & X2 that maximize value of Z. Max Z= X1 + 2X2 Subject to; 2 X1+ 5X2 >= 10 X1 + X2 = 0
Artificial Intelligence Answer only you know else skip otherwise sure report
Do not copy from other websites Correct and detailed answer will be Upvoted else downvoted. Thank you!
8. A school is creating class schedules for its students. The students submit their requested courses and then a program will be designed to find the optimal schedule for all students. The school has determined that finding the absolute best schedule cannot be solved in a reasonablo time. Instead they have decided to use a simpler algorithm that produces a good but non-optimal schedule in a more reasonable amount of time. Which principle does this decision best demonstrate? O A Unreasonable algorithms may sometimes also be undecidable O B. Heuristics can be used to solve some problems for which no reasonable algorithm exsts O C. efficiency Two algorithms that solve the same problem must also have the same O B. Approximate solutions are often identical to optimal solutions
Code (program)
Problem 1 Consider the following optimization problem: min f(x, y) = 3x² + y* x,y Solve the problem computationally - once by running gradient descent algorithm, and once by running the Newton descent algorithm. Report all parameters used in the two algorithms and the number of iterations to convergence. You have to use Python.
Prove that any LP optimization problem can be transformed into the following form: minimize 0 · x subject to Ax = b, x >= 0 If the LP is feasible, then it has an optimum value of 0 If the LP is not feasible, then it has an optimal value of infinity Explain what is the dual of this LP.
Q5/ by using Graphical Method to determine the optimal value of X1 & X2 that maximize value of Z. Max Z=5X1+ 7X2. Subject to: X1+X2 =0
I need the answer as soon as possible
need answer quickly but dont want existing one sure sure complaint