Xiao, Xinyue, Chen, Zhizhen ORCID: https://orcid.org/0000-0001-6656-5854, Quan, Lianfeng, Stojanovic, Aleksandar and Wu, Lijuan (2025) A knapsack modelling approach to financial resource allocation problem using a dual search pattern firefly algorithm. International Journal of Bio-Inspired Computation, 26 (5). pp. 1-13. ISSN 1758-0366 (Print), 1758-0374 (Online) (doi:10.1504/IJBIC.2025.149184)

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Abstract

The knapsack problem, a paradigm for constrained optimisation, underpins decision-making under scarcity in finance, logistics, and cognitive science. While classical methods (e.g., dynamic programming) handle small instances, real-world complexity demands metaheuristics like the firefly algorithm (FA), which balances exploration-exploitation trade-offs in dynamic, multi-objective scenarios (e.g., ethical resource allocation). Hybrid FA approaches integrating machine learning improve adaptability in noisy environments. Financial applications, however, lack frameworks addressing real-time responsiveness, ethical-risk synergies, and transparency. This study proposes a dual search pattern firefly algorithm based on Gaussian distribution and Lévy flights (DSPFA) for financial resource allocation, dynamically adapting to macroeconomic shifts, harmonising risk-return objectives with ethical imperatives (e.g., ESG criteria), and ensuring auditable decision pathways. Simulations demonstrate efficient optimisation of heterogeneous constraints (liquidity, compliance) with sublinear time complexity. By embedding fairness metrics and leveraging FA's global-local equilibrium, the framework advances ethical finance and portfolio management. Results highlight FA's scalability in evolving financial ecosystems and the knapsack model's versatility in modelling multidimensional trade-offs. This work bridges theoretical optimisation with practical challenges, offering stakeholders a tool for transparent, adaptive allocation under uncertainty.

Item Type:	Article
Uncontrolled Keywords:	knapsack model, metaheuristics, dual search pattern firefly algorithm, financial resource allocation
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce > HF5601 Accounting Q Science > QA Mathematics
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > Political Economy, Governance, Finance and Accountability (PEGFA) Journal of Economic Literature Classification > Political Economy, Governance, Finance and Accountability (PEGFA) Greenwich Business School > School of Accounting, Finance and Economics
Last Modified:	11 Nov 2025 10:19
URI:	https://gala.gre.ac.uk/id/eprint/51040

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