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Travelling salesman problem using dynamic programming in c
Travelling salesman problem using dynamic programming in c







travelling salesman problem using dynamic programming in c

total_num = 10 num_cities = SetCostMatrix(total_num) The below function sets the distance/cost matrix for the required number of cities that is passed as an argument. Multiple techniques are used to solve this problem:īrute Force Method: Find every possible combination of all the vertices.The diagonal values are 0 as the distance from the source to the source will always be 0. That's why these 2 problems are interconnected and solving one will solve the other. Actually, the Hamiltonian cycle is at the heart of the TSP. The Hamiltonian cycle problem can be converted to the Travelling Salesman Problem. The Hamiltonian cycle problem is NP-Hard. Given a graph, determine whether it contains a Hamiltonian cycle or not." "The cycle of visiting each vertex once in a graph, and returning to the starting vertex is known as a Hamiltonian cycle. The similar Hamiltonian cycle problem is: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?" The Travelling Salesman Problem belongs to the class of NP-Hard problems in combinatorial optimization. Introduction What is the Travelling Salesman Problem ? Quantum Simulation as a Search AlgorithmĮstimating Pi Using Quantum Phase Estimation Algorithm Grover's search with an unknown number of solutions Investigating Quantum Hardware Using Microwave PulsesĮxploring the Jaynes-Cummings Hamiltonian with Qiskit Pulse

travelling salesman problem using dynamic programming in c

Introduction to Quantum Error Correction using Repetition Codes

travelling salesman problem using dynamic programming in c

Investigating Quantum Hardware Using Quantum Circuits Solving the Travelling Salesman Problem using Phase Estimation Quantum Edge Detection - QHED Algorithm on Small and Large Images Quantum Image Processing - FRQI and NEQR Image Representations Implementations of Recent Quantum Algorithms Hybrid quantum-classical Neural Networks with PyTorch and Qiskit Solving Satisfiability Problems using Grover's Algorithm Solving combinatorial optimization problems using QAOA Solving Linear Systems of Equations using HHL Classical Computation on a Quantum Computer









Travelling salesman problem using dynamic programming in c