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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Asafuddoula, M. Ray, T. Isaacs, A. Singh, H.K. |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Eng. & Inf. Technol., Univ. of New South Wales at ADFA, Canberra, ACT, Australia (Asafuddoula, M.; Ray, T.; Singh, H.K.) || IBM Australia OzLabs, Canberra, ACT, Australia (Isaacs, A.) |
| Abstract | In this paper, we introduce a novel decomposition based steady state quantum genetic algorithm for the solution of engineering optimization problems. Systematic sampling is used to generate reference directions and a small population of quantum individuals (solutions with variables represented as Q-bits) is evolved using a simple variation operator. A solution represented using Q-bits has the ability to probabilistically represent a number of solutions defined through observation. We exploit the benefits of quantum representation within a steady state evolution scheme and illustrate the behavior of the algorithm using unconstrained DTLZ2 test problem involving 2, 3, 5, and 8 objectives and a set of multi/many-objective constrained engineering design optimization problems. The underlying motivation of quantum representation stems from its ability to represent multiple states which offers the potential to evolve a small population of solutions. This aspect is magnified even further when one attempts to solve a many objective optimization problem where evolution of a large population of solutions may not be practically viable. The proposed approach is expected to gain more attention in near future as quantum computing infrastructures become more readily available. |
| Starting Page | 893 |
| Ending Page | 899 |
| File Size | 423409 |
| Page Count | 7 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7256985 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Sociology Statistics Optimization Welding Genetic algorithms Steady-state Shafts |
| Content Type | Text |
| Resource Type | Article |
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