According to Professor Dan Ariely’s TED presentation on irrational decision making, the sales of the

According to Professor Dan Ariely’s TED presentation on irrational decision making, the sales of the middle configuration, i.e., Configuration 2, would expected be:

Create a sales forecast (in sales dollars) when no historicaldata is available. Use methods such as

Create a sales forecast (in sales dollars) when no historicaldata is available.    Use methods such as historicalanalogy, expert judgment, consumer surveys, the Delphi method, orcalculations based on population distributions, estimated growthrates, or expected market penetration rates to arrive at reasonablesales figures for your business for the next 5 years.  Pleasecomplete the Budget Proposal Doc. in the proper section which isnumebered in the table of contents and complete the budget propsalworkbook.xlsx.  This assignment is due on May 25, 2013 before11:00 PM EDT.

All of the following considerations used in designing service layouts EXCEPT: are a. Impulse purchas

All of the following considerations used in designing service layouts EXCEPT: are a. Impulse purchasing b. Speed up customer throughput c. Reduction of time to restock d. Ease of access to parking lot

Soap film problem Consider the soap film problem for which it is required to minimize where c, d…

Soap film problem Consider the soap film problem for which it is required to minimize

where c, d are constants, and that the end conditions are satisfied if (and only if) d = 0 and

where λ = a/c. Show that there are two admissible extremals provided that the aspect ratio b/a exceeds a certain critical value and none if b/a is less than this crirical value. Sketch a graph showing how this critical value is determined. The remainder of this question requires computer assistance. Show that the critical value of the aspect ratio b/a is about 1.51. Choose a value of b/a larger than the critical value (b/a = 2 is suitable) and find the two values of λ. Plot the two admissible extremals on the same graph. Which one looks like the actual shape of the soap film? Check your guess by perturbing each extremal by small admissible variations and finding the change in the value of the functional J[y].

 

Use TreePlan to solve this problem in Excel and submit your Excel spreadsheet here Use TreePlan to s

Use TreePlan to solve this problem in Excel and submit your Excel spreadsheet here

Use TreePlan to solve this problem in Excel and submit your Excel spreadsheet here

Use TreePlan to solve this problem in Excel and submit your Excel spreadsheet here

. The Americo Oil Company is considering making a bid for a shale oil development contract to be awarded by the federal government. The company has decided to bid $112 million. The company estimates that it has a 60% chance of winning the contract with this bid. If the firm wins the contract, it can choose one of three methods for getting the oil from the shale. It can develop a new method for oil extraction, use an existing (inefficient) process, or subcontract the processing to a number of smaller companies once the shale has been excavated. The cost of preparing the contract proposal is $2 million. If the company does not make a bid, it will invest in an alternative venture with a guaranteed profit of $30 million. Construct a sequential decision tree for this decision situation and determine whether the company should make a bid.

The results from these alternatives are as follows Use TreePlan to solve this problem in Excel Develop new process Profit ($1,000,000s) Probability Outcomes $600 Great success 30 Moderate success .60 300 Failure 10 -100 Use present process: Profit ($1,000,000s) Outcomes Probability .50 $300 Great success Moderate success 30 200 Failure 20 -40 Subcontract: Profit ($1,000,000s) Outcome Probability Moderate success 250 1.00

The safe operation of an automobile is dependent on several sub systems (e.g., engine,…

The safe operation of an automobile is dependent on several sub systems (e.g., engine, transmission, braking mechanism). Construct a cause-and-effect diagram for automobile accidents. Conduct a failure mode and effects criticality analysis and comment on areas of emphasis for prevention of accidents.

Constrained Optimization and Penalty Method Consider again the constrained minimization problem…

Constrained Optimization and Penalty Method

Consider again the constrained minimization problem having the objective function (E7.3.1a) and the constraints (E7.3.1b).

In Example 7.3, we made the MATLAB program “nm722.m” to solve the problem and defined the objective function (E7.3.2a) having the penalized constraint terms in the file named “f722p.m”.

(a) Whatisthe weighting coefficient vector v inthe file named “f722p.m”? Do the points reached by the routines “fminsearch()”/“opt_ steep()”/“fminunc()” satisfy all the constraints so that they are in the admissible region? If not, specify the constraint(s) violated by the points.

(b) Suppose the fourth constraint was violated by the point in (a). Then, how would you modify the weighting coefficient vector v so that the violated constraint can be paid more respect? Choose one of the following two weighting coefficient vectors:

(i) v = [1 1 1 1/3 1]

(ii) v = [1 1 1 3 1]

and modify the file “f722p.m” with this coefficient vector. Then, run the program “nm722.m”, fill in the 22 blanks of Table P7.8 with the results and see if the fourth constraint is still violated by the points reached by the optimization routines?

(c) Instead of the penalty method, apply the intrinsically constrained optimization routine “fmincon()” with the initial guesses x0 = [0.4 0.5] and [0.2 4] to solve the problem described by Eq. (E7.3.1) or (P7.8.1) and fill in Table P7.8 with the results concerning the reached point and the corresponding values of the objective/constraint functions.

(d) Based on the results listed in Table P7.8, circle the right word in each of the parentheses in the following sentences:

* For penalty methods, the non-gradient-based minimization routines like “Nelder()”/“fminsearch()” may work (better, worse) than the gradientbased minimization routines like “opt_steep()”/“fminunc()”. * If some constraint is violated, you had better (increase, decrease) the corresponding weight coefficient.

(cf) Besides, unconstrained optimization with the penalized constraints in the objective function sometimes works better than the constrained optimization routine “fmincon()”.

 

In Section 10.2.3, a formula for calculating PVE was given in Equation 10.8. We also saw that the… 1 answer below »

In Section 10.2.3, a formula for calculating PVE was given in Equation 10.8. We also saw that the PVE can be obtained using the sdev output of the prcomp() function. On the USArrests data, calculate PVE in two ways: (a) Using the sdev output of the prcomp() function, as was done in Section 10.2.3. (b) By applying Equation 10.8 directly. That is, use the prcomp() function to compute the principal component loadings. Then, use those loadings in Equation 10.8 to obtain the PVE

 

A rendering plant wishes to use the data (sales records from a few 5 local businesses and the month

A rendering plant wishes to use the data (sales records from a few 5 local businesses and the month of the year) to help determine their supply level for the coming months. The records shown in the table provide an excellent opportunity for you to assist them with their forecasting. Month S ales P nun-1:15 January 45 54.3 Febmaxgr 5? 63.8 March 32 395 April 44 49.9 Ma}; 51 513 June 34 39.9 What is the three-period weighted moving average forJuly using the weights 0.5 (most recent), 0.3, and 0.2?

Let X 1 , . . . , X n be a random sample from the P ois(θ) distribution and define λ =…

Let X1, . . . , Xn be a random sample from the P ois(θ) distribution and define λ = θ 1/a , a ≠ 0.

(a) Obtain the likelihood function l(λ; X).

(b) Obtain Jeffreys non-informative prior for λ.

(c) Obtain the Taylor expansion of L(λ; X) = log l(λ; X) around the maximum likelihood estimator of λ and determine the value(s) of a for which the 3rd order term vanishes.

(d) Discuss the importance of the result obtained in the previous item in terms of asymptotic theory.