The method is based on a population consisting of n vectors6 x0(k), . . . , xn(k), k is the generation/iteration of a method. In this section then notation x(i) is the ith element of vector x. The basic method depends on the following parameters • n—size of the population, • d—size of the xi vector, • C R ∈ [0, 1]—crossover probability, • F ∈ [0, 2]—mutation scale factor, also called differential weight. In each iteration a new population is generated in Which way for each member of population x.

Consider an n by n matrix, where each of the n2 entries is a positive integer. If the entries in this matrix are unsorted, then determining whether a target number t appears in the matrix can only be done by searching through each of the n2 entries. Thus, any search algorithm has a running time of O(n²). However, suppose you know that this n by n matrix satisfies the following properties: • Integers in each row increase from left to right. • Integers in each column increase from top to bottom. An example of such a matrix is presented below, for n=5. 4 7 11 15 2 5 8 12 19 3 6 9 16 22 10 13 14 17 24 1 18 21 23 | 26 | 30 Here is a bold claim: if the n by n matrix satisfies these two properties, then there exists an O(n) algorithm to determine whether a target number t appears in this matrix. Determine whether this statement is TRUE or FALSE. If the statement is TRUE, describe your algorithm and explain why your algorithm runs in O(n) time. If the statement is FALSE, clearly explain why no…

| Consider the elliptic curve group based on the equation y? = x' + ax + b mod p where a = 4, b = 1, and p = 7. This curve contains the point P = (0, 1). The order of this elliptic curve group is the prime number 5, and therefore we can be sure that P is a primitive element. Another element in this group is Q = (0,6). The index of Q with respect to P is the least positive integer d such that Q = dP. What is d, the index of Q?

Consider the problem of making change for n cents using the fewest number of coins. Assume that we live in a country where coins come in k dierent denominations c1, c2, . . . , ck, such that the coin values are positive integers, k ≥ 1, and c1 = 1, i.e., there are pennies, so there is a solution for every value of n. For example, in case of the US coins, k = 4, c1 = 1, c2 = 5, c3 = 10, c4 = 25, i.e., there are pennies, nickels, dimes, and quarters. To give optimal change in the US for n cents, it is sufficient to pick as many quarters as possible, then as many dimes as possible, then as many nickels as possible, and nally give the rest in pennies.   Design a bottom-up (non-recursive) O(nk)-time algorithm that makes change for any set of k different coin denominations. Write down the pseudocode and analyze its running time. Argue why your choice of the array and the order in which you fill in the values is the correct one. Notice how it is a lot easier to analyze the running time of…

1(a). For an M/M/1 queuing system, write your own function in R to compute andoutput the:1. long-run probability po,p1,…,pn of there being 0,..,n people in the system.2. the values L, Lq, W, Wq, and Wse. The function should return elements with the names probs (vector of po,…,pn), L, Lq, W,Wq, and Wse (does not have to be in this order) The function should take as inputs, lambda (arrival rate), mu (service rate), and n (thenumber of people to compute probabilities for 0,…,n) Note: you are to code the computations for the above on your own, so none of the functionsin the queueing package are to be used. 1(b).  Using your function from 1(a), find the values (b)-(f) in the Queuing Theory(M_M_1).

I am trying to work with some generic search algorithms in a coding homework, and I am having trouble understanding some of it. Here are my questions:   1. For this linear search algorithm below I am trying to send an array of x and y cordinate points into it and search to see if a specific x, y point is in the array, but I don't know how to send the points into the linear search function. By the way, I am using a struct point type for the array of points and the point I am looking for. (The below code is an exact example from our teacher during a lecture.)   void* linearSearchG(void* key, void* arr, int size, int elemSize, int(*compare)(void* a, void* b)) {   for (int i = 0; i < size; i++) {   void* elementAddress = (char*)arr + i * elemSize; if (compare(elementAddress, key) == 0) return elementAddress; } return NULL; }     2. I forgot what this line of code specifically does: void* elementAddress = (char*)arr + i * elemSize;   I need to code this myself, so if you could explain…