@inproceedings{56261bb6841342acbd71b6aaaa146a8b,
title = "Applying hueristic algorithms to portfolio selection problem",
abstract = "In this paper, we solve the portfolio selection problem. In our approach, we first propose a modified immune algorithm (IA) to reuse the memory cells we got in earlier stages, so that more information can be utilized in the next stages. Our experimental results show that the modified IA can successfully obtain significantly higher return than genetic algorithm (GA) and particle swarm optimization (PSO). Second, we also propose a hybrid of IA and PSO (IA-PSO), and a hybrid of GA and PSO. From our experiments, the hybrid IA-PSO maintains the high return while becoming more stable.",
keywords = "bootstrapping, genetic algorithm, immune algorithm, particle swarm optimization, portfolio selection problem",
author = "Kang, {Po Ya} and I-Chen Wu and Hsueh, {Chu Hsuan}",
year = "2016",
month = feb,
day = "12",
doi = "10.1109/TAAI.2015.7407064",
language = "English",
series = "TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "323--329",
booktitle = "TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence",
address = "United States",
note = "null ; Conference date: 20-11-2015 Through 22-11-2015",
}