Papers by soham mukherjee
International Journal in Foundations of Computer Science & Technology
ABSTRACT
This Paper provides a brief description of the Genetic Algorithm (GA), the Simulated An... more 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 our
Proposed Genetic Algorithm (GA), Proposed Simulated Annealing (SA) Algorithm using GA, Classical Backtracking
(BT) Algorithm and Classical 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.
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Papers by soham mukherjee
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 our
Proposed Genetic Algorithm (GA), Proposed Simulated Annealing (SA) Algorithm using GA, Classical Backtracking
(BT) Algorithm and Classical 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.