Fatemeh Jalalvand

Orcid: 0000-0003-1335-2139

According to our database1, Fatemeh Jalalvand authored at least 12 papers between 2017 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2026
Machine learning integrated multi-objective simulation-based optimization for a personnel planning, asset management and fleet renewal problem.
Comput. Ind. Eng., 2026

2025
LLMs in the SOC: An Empirical Study of Human-AI Collaboration in Security Operations Centres.
CoRR, August, 2025

Adaptive alert prioritisation in security operations centres via learning to defer with human feedback.
CoRR, June, 2025

Alert Prioritisation in Security Operations Centres: A Systematic Survey on Criteria and Methods.
ACM Comput. Surv., February, 2025

2024
Towards Human-AI Teaming to Mitigate Alert Fatigue in Security Operations Centres.
ACM Trans. Internet Techn., 2024

2023
A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems.
J. Glob. Optim., June, 2023

2022
A joint problem of strategic workforce planning and fleet renewal: With an application in defense.
Eur. J. Oper. Res., 2022

2021
A multi-objective simulation-optimization for a joint problem of strategic facility location, workforce planning, and capacity allocation: A case study in the Royal Australian Navy.
Expert Syst. Appl., 2021

Integrating decision maker preferences to a risk-averse multi-objective simulation-based optimization for a military workforce planning, asset management and fleet management problem.
Comput. Ind. Eng., 2021

2020
Solving Strategic Military Workforce Planning Problems with Simulation-optimization.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

A Multi-objective Risk-averse Workforce Planning under Uncertainty.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

2017
A hierarchical multi-criteria group decision-making method based on TOPSIS and hesitant fuzzy information.
Int. J. Appl. Decis. Sci., 2017


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