An improved quantum genetic algorithm for the Resource Constrained Project Scheduling

DOI

10.2991/iceeecs-16.2016.122How to use a DOI?

Keywords

Quantum computing; quantum genetic algorithm; resource-constrained; project scheduling

Abstract

In this paper, proposes an improved quantum genetic algorithm based on RCPSP. Project implementation process often involves the sharing of resources and conflicts between the different projects, so in the case of how resource-constrained project scheduling resources to meet the requirements of different projects and shorten the duration of each project is an important issue. Algorithm is based on the priority activities quantum encoding, combined with adjacency matrix storage activities, effectively solved the phenomenon of illegal activity scheduling, using preemptive mode of resource allocation to schedule resources, thus avoiding resource allocation conflicts problem. Experiments show that, through multiple iterations of the computer's parallel computing can be effectively come to meet the multi-project resource constrained scheduling.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mingliang Li
AU  - Xueyan Song
PY  - 2016/12
DA  - 2016/12
TI  - An improved quantum genetic algorithm for the Resource Constrained Project Scheduling
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 612
EP  - 617
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.122
DO  - 10.2991/iceeecs-16.2016.122
ID  - Li2016/12
ER  -