A Comparison of a Hyper-Heuristic and an EA on the Portfolio Optimisation Problem

Rahul Soni; Matthew Craven; David Walker

A Comparison of a Hyper-Heuristic and an EA on the Portfolio Optimisation Problem

Rahul Soni, Matthew Craven^*, David Walker

^*Corresponding author for this work

School of Engineering, Computing and Mathematics

University of Exeter

Research output: Contribution to conference › Conference paper (not formally published)

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Abstract

We analyse a selection hyper-heuristic (SHH) and NSGAII for the multi-objective cardinality constrained portfolio optimisation problem, an NP-hard problem addressing the asset allocation trade-off between return and risk under constraints of the number of assets. We evaluated the performance of the SHH and NSGA-II for cardinality constraints K = {2, 5}. Our results are competitive with those of NSGA-II.

Original language	English
Publication status	Published - 31 Aug 2025
Event	24th UK Workshop in Computational Intelligence - Edinburgh Napier University, Edinburgh, United Kingdom Duration: 3 Sept 2025 → 5 Sept 2025 https://ukci2025.napier.ac.uk/index.php

Workshop

Workshop	24th UK Workshop in Computational Intelligence
Abbreviated title	UKCI 2025
Country/Territory	United Kingdom
City	Edinburgh
Period	3/09/25 → 5/09/25
Internet address	https://ukci2025.napier.ac.uk/index.php

ASJC Scopus subject areas

Artificial Intelligence
Control and Optimization

Keywords

Evolutionary Algorithm
Hyper-heuristics
Metaheuristics
Combinatorial Problems
Portfolio Optimisation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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UKCI_2025_paper_71Final published version, 655 KB

Cite this

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title = "A Comparison of a Hyper-Heuristic and an EA on the Portfolio Optimisation Problem",

abstract = "We analyse a selection hyper-heuristic (SHH) and NSGAII for the multi-objective cardinality constrained portfolio optimisation problem, an NP-hard problem addressing the asset allocation trade-off between return and risk under constraints of the number of assets. We evaluated the performance of the SHH and NSGA-II for cardinality constraints K = \{2, 5\}. Our results are competitive with those of NSGA-II.",

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T1 - A Comparison of a Hyper-Heuristic and an EA on the Portfolio Optimisation Problem

AU - Soni, Rahul

AU - Craven, Matthew

AU - Walker, David

PY - 2025/8/31

Y1 - 2025/8/31

N2 - We analyse a selection hyper-heuristic (SHH) and NSGAII for the multi-objective cardinality constrained portfolio optimisation problem, an NP-hard problem addressing the asset allocation trade-off between return and risk under constraints of the number of assets. We evaluated the performance of the SHH and NSGA-II for cardinality constraints K = {2, 5}. Our results are competitive with those of NSGA-II.

AB - We analyse a selection hyper-heuristic (SHH) and NSGAII for the multi-objective cardinality constrained portfolio optimisation problem, an NP-hard problem addressing the asset allocation trade-off between return and risk under constraints of the number of assets. We evaluated the performance of the SHH and NSGA-II for cardinality constraints K = {2, 5}. Our results are competitive with those of NSGA-II.

KW - Evolutionary Algorithm

KW - Hyper-heuristics

KW - Metaheuristics

KW - Combinatorial Problems

KW - Portfolio Optimisation

UR - https://pearl.plymouth.ac.uk/secam-research/2164/

M3 - Conference paper (not formally published)

T2 - 24th UK Workshop in Computational Intelligence

Y2 - 3 September 2025 through 5 September 2025

ER -

A Comparison of a Hyper-Heuristic and an EA on the Portfolio Optimisation Problem

Abstract

Workshop

ASJC Scopus subject areas

Keywords

UN SDGs

Access to Document

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