A problem that can be solved in polynomial time by some non-deterministic algorithms is in class. (P, NP)

Solve the following exercise using jupyter notebook for Python, to find the objective function, variables, constraint matrix and print the graph with the optimal solution. Use linear programming methods to solve this problem. Represent the constraints and the objective function mathematically in code. Use Python and the SciPy and Matplotlib libraries to solve the problem and visualize the optimal solution on a graph. Clearly state the optimal solution and any assumptions made while solving the problem.   A farm specializes in the production of a special cattle feed, which is a mixture of corn and soybeans. The nutritional composition of these ingredients and their costs are as follows: - Corn contains 0.09 g of protein and 0.02 g of fiber per gram, with a cost of.$0.30 per gram.- Soybeans contain 0.60 g of protein and 0.06 g of fiber per gram, at a cost of $0.90 per gram.0.90 per gram. The dietary needs of the specialty food require a minimum of 30% protein and a maximum of 5% fiber.…

Prove this issue is NP-complete:   S and t are integer integers. Does S have a subset with a t-sum?   Data Structures and Algorithm issue

An NP-complete problem is a fascinating kind of problem because till now no one has discovered the polynomial-time algorithm to solve it and also no one has proved that no polynomial-time algorithm can exist for any NP-complete problem. It is an open research problem since it was first posed in 1971 to prove P#NP. The NxN Queens problem can be summarized as follows: putting N chess queens on an N×N chessboard such that none of them is able to attack any other queen using the standard chess queen's moves (row-column- diagonal). Thus, a solution requires that no two queens share the same row, column, or diagonal. Solutions exist only for N = 1 or N 2 4. Use the given function below to test whether a queen is attacked by another or not. You are not allowed to use any other code to check if a queen is safe. Implement a backtracking solution for the algorithm in Java that finds all possible solutions for N queens and measure the execution time it takes for N=4 to 12 and compare them…

Coin exchange problem generate algorithmic solutions to the problems, with each of the following algorithm design techniques, in the Python language. - Greedy Algorithms - Dynamic Programming - Backtracking - Branch and Bound

Outline a polynomial-time algorithm that verifies whether or not a proposed solution solves the problem. Describe your algorithm in English step by step and explain why it is in polynomial time. knapsack problem bin packing problem

0/1 knapsack problem, generate algorithmic solutions to this problem, with each of the design techniques, of the following algorithms, in Python language: - greedy algorithms - dynamic programming - backtracking - branching and pruning (brach and bound) We have n objects, each with a weight (w_i) and a benefit (v_i), and a backpack in which we can put objects, with a maximum weight capacity M. The objective is to maximize the benefit of the transported objects, where each object can be taken integer (x_i=1) or nothing (x_i=0).

If you are given a set S of integers and a number t, prove that this issue falls into the NP class. Is there a subset of S where the total number of items is t? Note: Complexity in Data Structures and Algorithms

A recursive algorithm is applied to some data A = (a₁,..., am) where m≥ 2. The running time T is characterised using the following recurrence equations: T(2) = c when the size of A is 2 T(m) = T(m-1) + 2c otherwise Determine the running time complexity of this algorithm.