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Two-Dimensional Quantum Genetic Algorithm: Application to Task Allocation Problem
Sabyasachi Mondal1, Antonios Tsourdos1
1School of Aerospace, Transport and Manufacturing (SATM), Cranfield University, Cranfield MK430AL, UK.
Abstract:
This paper presents a Two-Dimensional Quantum Genetic Algorithm (2D-QGA), which is a new variety of QGA. This variety will allow the user to take the advantages of quantum computation while solving the problems which are suitable for two-dimensional (2D) representation or can be represented in tabular form. The performance of 2D-QGA is compared to two-dimensional GA (2D-GA), which is used to solve two-dimensional problems as well. The comparison study is performed by applying both the algorithm to the task allocation problem. The performance of 2D-QGA is better than 2D-GA while comparing execution time, convergence iteration, minimum cost generated, and population size.
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