Asap The following tableau was obtained after several steps of the simplex algorithmin a standard linear programming problem. What conclusions can you draw formit?X2x3X4RHSRatio161309.1473110x1 should enter the basisx2 should leave the basisThis is the final tableau with optimal x0 and x = 0x_4^*=0The first line is to be read as Z:6x1 + x3 + 30The optimal value of Z is 30

From the given tableau we can say that, All the entries are non negative which is for maximization…

The following tableau was obtained after several steps of the simplex algorithm in a standard linear programming problem. What conclusions can you draw form it? X2 x3 X4 RHS Ratio 1 6 1 30 9. 1 7 1 10 x1 should enter the basis x2 should leave the basis This is the final tableau with optimal x = 0 and æ = 0 x_4^*=0 The first line is to be read as Z 6x1 + x3 + 30 The optimal value of Z is 30

The following tableau was obtained after several steps of the simplex algorithm in a standard linear programming problem. What conclusions can you draw form it? X2 x3 X4 RHS Ratio 1 6 1 30 9. 1 7 1 10 x1 should enter the basis x2 should leave the basis This is the final tableau with optimal x = 0 and æ = 0 x_4^*=0 The first line is to be read as Z 6x1 + x3 + 30 The optimal value of Z is 30

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter2: Systems Of Linear Equations

Section2.2: Direct Methods For Solving Linear Systems

Problem 2CEXP

See similar textbooks

Similar questions

An advertising firm has D dollars to spend on reachingcustomers in T separate markets. Market t consists of ktpeople. If x dollars are spent on advertising in market t, theprobability that a given person in market t will be reachedis pt(x). Each person in market t who is reached will buy ctunits of the product. A person who is not reached will notbuy any of the product. Formulate a dynamic programmingrecursion that could be used to maximize the expectednumber of units sold in T markets.
Although the Hungarian method is an efficient methodfor solving an assignment problem, the branch-and-boundmethod can also be used to solve an assignment problem.Suppose a company has five factories and five warehouses.Each factory’s requirements must be met by a singlewarehouse, and each warehouse can be assigned to only onefactory. The costs of assigning a warehouse to meet afactory’s demand (in thousands) are shown in Table 77.Let xij 1 if warehouse i is assigned to factory j and 0otherwise. Begin by branching on the warehouse assigned tofactory 1. This creates the following five branches: x11 1,x21 1, x31 1, x41 1, and x51 1. How can we obtaina lower bound on the total cost associated with a branch?Examine the branch x21 1. If x21 1, no furtherassignments can come from row 2 or column 1 of the costmatrix. In determining the factory to which each of theunassigned warehouses (1, 3, 4, and 5) is assigned, we cannotdo better than assign each to the smallest cost in…
We have an initial simplex tableau given by
The owner of the Consolidated Machine Shop has $10,000 available to purchase a lathe, a press, a grinder, or some combination thereof. The following 0–1 integer linear programming model has been developed to determine which of the three machines (lathe, x1, press, x2, or grinder, x3) should be purchased in order to maximize annual profit: Maximize Z = 1000x1 + 700x2 + 800x3 (profit, $) subject to: $5,000x1 + 6,000x2 + 4,000x3 ≤ 10,000 (cost, $) x1 , x2 , x3 = 0 or 1 1. Solve this model by using the computer.
MSA Computer Corporation manufactures two models of minicomputers, the Alpha 4 and the Beta 5. The firm employs five technicians, working 160 hours each per month, on its assembly line. Management insists that full employment (i.e., all 160 hours of time) be maintained for each worker during next month’s operations. It requires 20 labor hours to assemble each Alpha 4 computer and 25 labor hours to assemble each Beta 5 model. MSA wants to see at least 10 Alpha 4s and at least 15 Beta 5s produced during the production period. Alpha 4s generate $1,200 profit per unit, and Beta 5s yield $1,800 each. Determine the most profitable number of each model of minicomputer to produce during the coming month.
If dfBetween = 3, dfWithin = 10, MSWithin = 34.19, MSBetween = 2.11, and α = .01 and two groups have three cases and two groups have four cases, what is Tukey's HSD value? (One will need to refer to a Tukey table of critical values to solve this.)
Use Simplex Algorithm to determine the optimal solution of this LP problem. Maximize z = 2x1 − x2 + 2x3subject to:2x1 + x2 ≤ 10x1 + 2x2 − 2x3 ≤ 20x2 + 2x3 ≤ 5x1, x2, x3 ≥ 0
to run 2k factorial design in 8 blocks it is necessary to select 3 factors or interactions to form the blocks. as a result there will be a yotal number of effects confounded with blocks equal to
Consider the 8-city traveling salesman problem whose links have the associated distances shown in the following table (where a dash indicates the absence of a link). City 1 is the home city. Using 1-2-3-4-5-6-7-8-1 as the initial trial solution, perform three iterations of simulated annealing algorithm.
A shop has four machinists to be assigned to four machines. The hourly cost of having each machine operated by each machinist is as follows: However, because he does not have enough experience, machinist 3 cannot operate machine B. a. Determine the optimal assignment and compute total minimum cost. b. Formulate this problem as a general linear programming model.
The space shuttle is about to go up on another flight.With probability pt(z), it will use z type t fuel cells duringthe flight. The shuttle has room for at most W fuel cells. Ifat any time during the flight, all the type t fuel cells burnout, a cost ct will be incurred. Assuming the goal is tominimize the expected cost due to fuel cell shortages, set upa dynamic programming model that could be used todetermine how to stock the space shuttle with fuel cells.There are T different types of fuel cells.
we are going to use linear programming to develop a simple machinelearning algorithm to help us classify data points. Training data and Test data.Each of the 20 data points in the training data consists of 2 sensor readings x1, x2 whichare real numbers corresponding to the readout of two sensors during an event and a classi-cation y which is either 0 or 1, 0 indicates the event corresponding to the sensor data wasdetermined to not be a gravitational wave and a 1 indicates the event was determined tobe a gravitational wave. Thus, a typical line in the le looks something like:0.0 78.1 60.6Which indicates the 2 sensors had readings 78.1, 60.6 respectively, and the 0.0 indicatesno gravitational wave was observed. The test data consists again of sensor readings xi but with no classication y provided.Your job is to use the training data to develop a model that can take in sensor data andpredict the classication (again, 0 or 1). You will then run your model on the 20 points inthe test…