Two-Dimensional Quantum Genetic Algorithm: Application to Task Allocation Problem

被引：3

作者：

Mondal, Sabyasachi ^{[1
]}

Tsourdos, Antonios ^{[1
]}

机构：

[1] Cranfield Univ, Sch Aerosp Transport & Mfg SATM, Cranfield MK4 30AL, Beds, England

来源：

SENSORS | 2021年 / 21卷 / 04期

基金：

英国工程与自然科学研究理事会;

关键词：

Quantum Genetic Algorithm; two-dimensional quantum chromosome; task allocation; OPTIMIZATION;

D O I：

10.3390/s21041251

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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.

引用

页码：1 / 24

页数：24

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