%0 Journal Article %1 noauthororeditor %A Mukherjee, Soham %A Datta, Santanu %A Chanda, Pramit Brata %A Pathak, Pratik %D 2015 %J International Journal on Foundations of Computer Science & Technology (IJFCST) %K Algorithm Annealing Backtracking Brute Fitness Force Genetic Intractable N No Problem Problems Queens Search Simulated Solutions Time Tractable and of %N 2 %P 13 %R 10.5121/ijfcst.2015.5202 %T COMPARATIVE STUDY OF DIFFERENT ALGORITHMS TO SOLVE N QUEENS PROBLEM %U https://wireilla.com/papers/ijfcst/V5N2/5215ijfcst02.pdf %V 5 %X This Paper provides a brief description of the Genetic Algorithm (GA), the Simulated Annealing (SA) Algorithm, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm and attempts to explain the way as how the Proposed Genetic Algorithm (GA), the Proposed Simulated Annealing (SA) Algorithm using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm can be employed in finding the best solution of N Queens Problem and also, makes a comparison between these four algorithms. It is entirely a review based work. The four algorithms were written as well as implemented. From the Results, it was found that, the Proposed Genetic Algorithm (GA) performed better than the Proposed Simulated Annealing (SA) Algorithm using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm and it also provided better fitness value (solution) than the Proposed Simulated Annealing Algorithm (SA) using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm, for different N values. Also, it was noticed that, the Proposed GA took more time to provide result than the Proposed SA using GA.

@article{noauthororeditor, abstract = {This Paper provides a brief description of the Genetic Algorithm (GA), the Simulated Annealing (SA) Algorithm, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm and attempts to explain the way as how the Proposed Genetic Algorithm (GA), the Proposed Simulated Annealing (SA) Algorithm using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm can be employed in finding the best solution of N Queens Problem and also, makes a comparison between these four algorithms. It is entirely a review based work. The four algorithms were written as well as implemented. From the Results, it was found that, the Proposed Genetic Algorithm (GA) performed better than the Proposed Simulated Annealing (SA) Algorithm using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm and it also provided better fitness value (solution) than the Proposed Simulated Annealing Algorithm (SA) using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm, for different N values. Also, it was noticed that, the Proposed GA took more time to provide result than the Proposed SA using GA. }, added-at = {2023-10-19T15:10:11.000+0200}, author = {Mukherjee, Soham and Datta, Santanu and Chanda, Pramit Brata and Pathak, Pratik}, biburl = {https://www.bibsonomy.org/bibtex/2c29456b091b945ac414a5d3a127b5e21/devino}, doi = {10.5121/ijfcst.2015.5202}, interhash = {cddf88525928bbe94ab1ee91a911f63c}, intrahash = {c29456b091b945ac414a5d3a127b5e21}, issn = {ISSN : 1839-7662}, journal = {International Journal on Foundations of Computer Science & Technology (IJFCST)}, keywords = {Algorithm Annealing Backtracking Brute Fitness Force Genetic Intractable N No Problem Problems Queens Search Simulated Solutions Time Tractable and of}, month = mar, number = 2, pages = 13, timestamp = {2023-10-19T15:10:11.000+0200}, title = {COMPARATIVE STUDY OF DIFFERENT ALGORITHMS TO SOLVE N QUEENS PROBLEM}, url = {https://wireilla.com/papers/ijfcst/V5N2/5215ijfcst02.pdf}, volume = 5, year = 2015 }