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- The Manhattan Tourist Problem (1) Given setting in Figure 6.4, calculate exact number of different paths by dynamic programming. (2) For a general setting, i.e., from source(0,0) to sink (n, m), how many different paths by dynamic programming?1 4 3 3 4 1 0 4 3 N 5 1How exactly would I be able to paraphrase this pseudo-code so that it can make a bit more sense? 1.Initialtzation: generate a random solution X ← RandomSolution() 2. Solve the traffic assignment problem at equilibrium for each link: (flow, cost) ← NonLinearComplementary(X) 3. Evaluate the objective value for the current solution: f (X) ← EvaluateObj Val (f low, cost) 4. T ← Tmax 5 while (T > Tmin) do 6 I ← 1 7 while (t < ltermax)do 8 X' ← FindNeighborSolution(X) 9 (flow,cost) ← NonLinearComplementary(X') 10 f(X') ← EvaluateObf Val (f low, Cost) 11 Δ ←(f(x) - f(x')) 12 if(Δ<0)then 13 BoltzmannValue ← exp(-Δ/T) 14 if (BoltzmannValue < Random (0,1)) then 15 Accept the new solution: X ← X' 16 end If 17 Else I8 Accept the new solution: X ← X' 19 end if 20 i ← i+1 21 end while 22 T ←T ∞ 23 end while ________Assume now that there are 12 people initially on the yacht with 6 women and 6 men, and that exploration teams consist of six people. How many exploration teams have more women than men?
- Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of it’s hyper parameter. Based upon that give the answer for following question. What would happen when you use very large value of C(C->infinity)? Note: For small C was also classifying all data points correctly Group of answer choices a. We can still classify data correctly for given setting of hyper parameter C b. We can not classify data correctly for given setting of hyper parameter C c. Can’t Say d. None of theseProblem 3: Consider the ICT bot in this 3*3 grid. Y X 1 2 3 1 S 2 3 * E S is the location where the robot starts.E is the end location where the robot must find * and carry to E. The robot can perform two actions: move and retrieve_star. It can move in 4 directions 1 adjacent cell at a time, from (x,y) to (x+1,y), (x-1,y),(x,y+1), and (x,y-1) as long as it remains on the 3*3 grid. Upon each grid, the robot will receive the signal from its sensor if * is in the current grid or not. If * is in the current grid, it can retrieve * using the retrieve_star command. 1) Design a classical representation for the current planning problem.Following on your job in modelling the employee assignments from the previous practical, you’ve now obtained the following business rules: One Employee supervises Many Employees, and possibly none, and a max of 20. One Employee is supervised by One Employee, and not none. One Employee takes on Many Assignments, and possibly none. One Assignment is taken on by One Employee, and not none. One Assignment takes place in One Section, and not none. One Section appears in Many Assignments, and possibly none. One Section belongs to One Building, and not none. One Building has Many Sections, and possibly none, and a max of 20. You have also been given a small sample of their records, in case this may prove useful. It is below. Assignment No Date Employee No Employee Section Section N Building Start End Supervisor No Building N 8 22/08/2013 2111 B. Johns G1 Canteen G Willis 12h00 19h00 2321 2 9 23/08/2013 2111 B. Johns F3…
- It has been observed by management that some faculty members at theuniversity demonstrate a lackadaisical attitude toward teaching. They seldom go to class yet at the end of each month they receive full salary. Management has decided that GHs 200, 300, 400, and 500 will be deducted from a faculty’s salary if he/she offends once, twice, third time and forth time respectively in a month. This means that if a faculty member offends once in a month GHs200 will be deducted, if a faculty member offends twice in a month, GHs 500 (i.e. 200+300) will be deducted, if a faculty member offends three times in a month GHs 900 (i.e. 200+300+400), will be deducted and if a faculty member offends four times in a month GHs 1,400 (i.e. 200+300+400+500). Assuming all faculty members are on a flat salary rate of GHs 2000.a. Write a program to request for the names of four faculty members and number times he/she has absented him/herself from class in a month.One of them should have absented him/herself…Solution B ?A contractor owns three excavators of different capacity. He/she wants to dispatch these excavatorsinto three different jobs. The performance of the excavators is measured as the time consumed toperform each job. The data of the time tests are shown as given in the table below. (a) Draw a network flow diagram.(b) Formulate a mathematical model to obtain the minimum time.(c) Solve this model using the Vogel’s approximation model.
- A firm is considering projects A, B, . . . , H. Using binary variables x_a, ..., x_h and linear constraints, model the following conditions on the projects to be undertaken. At most one of A,B,...,H. Exactly two of A,B,...,H. If A then B. If A then not B. If not A then B. If A then B and C. If A then B, and if B then A. If A then B or C. If B or C then A. If B and C then A. If two or more of B,C,D,E then A. If m or more than n projects B,...,H then A.A blood bank wants to determine the least expensive way to transport available blood donations from Pittsburgh and Staunton to hospitals in Charleston, Roanoke, Richmond, Norfolk, and Suffolk. The supply and demand for donated blood is shown in the figure along with the unit cost of shipping along each possible arc. Provide the complete linear programing formulation. Clearly specify decision variables, objective function and constraints. Build a model in Excel and paste a screenshot here. Use “FORMULATEXT” in your model to show calculations. According to Excel Solver, what is the optimal transportation plan for blood bank? What is the minimum total shipping cost?In the Green Grass shipping model, we currently assume that if a customer’s order is satisfied, it must be satisfied from a single plant. Suppose instead that it can be satisfied from more than one plant. For example, if the company decides to satisfy Dallas’s order, it could ship part of this order from Denver and part from Phoenix (or some other combination of open plants). Continue to assume, however, that the company must satisfy either all or none of each customer’s order. Modify the model appropriately and use Solver to solve it. Does the solution change?