Abdullah, M., Siraj, S., & Hodgett, R. (2021). An Overview of Multi-Criteria Decision Analysis (MCDA) Application in Managing Water-Related Disaster Events: Analyzing 20 Years of Literature for Flood and Drought Events. Water, 13(10). https://doi.org/10.3390/w13101358

Abel, E., & Siraj, S. (2022, October 21). How fair were COVID-19 restriction decisions? A data-driven investigation of England using the dominance-based rough sets approach. https://doi.org/10.48550/arxiv.2211.00056

Abel, E., & Siraj, S. (2024). An approach to investigate fairness using Dominance-based Rough Sets Analysis—How fair were the COVID-19 restriction decisions in the UK? Applied Soft Computing, 151(111121). https://doi.org/10.1016/j.asoc.2023.111121

Abel, E., & Siraj, S. (2025). Fairness and Trust in Data-Driven Decisions: Analyzing Discrepancies in Ordinal Decisions. 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), 1–7. https://doi.org/10.1109/citrex64975.2025.10974938

Ahmed, W., Khan, B., Ullah, Z., Mehmood, F., Ali, S., Edifor, E., Siraj, S., & Nawaz, R. (2022). Stochastic adaptive-service level agreement-based energy management model for smart grid and prosumers. PLoS One, 17(12). https://doi.org/10.1371/journal.pone.0278324

Ali, Y., Khalid, O., Khan, I., Hussain, S., Rehman, F., Siraj, S., & Nawaz, R. (2022). A hybrid group-based movie recommendation framework with overlapping memberships. PLoS One, 17(3). https://doi.org/10.1371/journal.pone.0266103

Araújo, A., Mota, C., & Siraj, S. (2023). Using Genetic Programming to Identify Characteristics of Brazilian Regions in Relation to Rural Credit Allocation. Agriculture, 13(5). https://doi.org/10.3390/agriculture13050935

Bukhari, S., Rehmani, M., & Siraj, S. (2014). Channel Bonding in Cognitive Radio Sensor Networks. In Advances in Wireless Technologies and Telecommunication (pp. 99–126). IGI Global. https://doi.org/10.4018/978-1-4666-6212-4.ch005

Bukhari, S., Rehmani, M., & Siraj, S. (2016). A Survey of Channel Bonding for Wireless Networks and Guidelines of Channel Bonding for Futuristic Cognitive Radio Sensor Networks. IEEE Communications Surveys and Tutorials, 18(2), 924–948. https://doi.org/10.1109/COMST.2015.2504408

Bukhari, S., Rehmani, M., & Siraj, S. (2017, May 3). Remaining Idle Time Aware Intelligent Channel Bonding Schemes for Cognitive Radio Sensor Networks. https://doi.org/10.48550/arxiv.1705.01261

Bukhari, S., Rehmani, M., & Siraj, S. (2019). Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks. Wireless Networks, 25(8), 4523–4539. https://doi.org/10.1007/s11276-018-1745-9

Bukhari, S., Siraj, S., & Rehmani, M. (2016). PRACB: A Novel Channel Bonding Algorithm for Cognitive Radio Sensor Networks. IEEE Access, 4. https://doi.org/10.1109/ACCESS.2016.2618418

Bukhari, S., Siraj, S., & Rehmani, M. (2018a). NS-2 based simulation framework for cognitive radio sensor networks. Wireless Networks, 24(5), 1543–1559. https://doi.org/10.1007/s11276-016-1418-5

Bukhari, S., Siraj, S., & Rehmani, M. (2018b). Wireless Sensor Networks in Smart Cities: Applications of Channel Bonding to Meet Data Communication Requirements. In H. Mouftah, M. Erol-Kantarci, & M. Hussain Rehmani (Eds.), Transportation and Power Grid in Smart Cities: Communication Networks and Services. Wiley.

Choicharoon, A., Hodgett, R., Summers, B., & Siraj, S. (2024). Hit or miss: A decision support system framework for signing new musical talent. European Journal of Operational Research, 312(1), 324–337. https://doi.org/10.1016/j.ejor.2023.06.014

Dean Pelegrina, G., & Siraj, S. (2024). Shapley value-based approaches to explain the quality of predictions by classifiers. IEEE Transactions on Artificial Intelligence, 1–15. https://doi.org/10.1109/tai.2024.3365082

Gong, C., Siraj, S., Yu, L., & Fu, L. (2024). A generalized form of the distance-induced OWA operators – Demonstrating its use for evaluation indicator system in China. Expert Systems with Applications, 247(123257). https://doi.org/10.1016/j.eswa.2024.123257

Greco, S., Siraj, S., & Lundy, M. (2021, July 4). Supporting decisions by unleashing multiple mindsets using pairwise comparisons method. https://doi.org/10.48550/arxiv.2107.01731

Greco, S., Siraj, S., & Lundy, M. (2022, January 1). Supporting Decisions by Unleashing Multiple Mindsets Using Pairwise Comparisons Method. Elsevier. https://doi.org/10.2139/ssrn.4171607

Hodgett, R., & Siraj, S. (2019). SURE: A method for decision-making under uncertainty. Expert Systems with Applications, 115, 684–694. https://doi.org/10.1016/j.eswa.2018.08.048

Hodgett, R., Siraj, S., & Hogg, E. (2024). Smart decisions: A structured approach to decision analysis using MCDA. https://doi.org/10.1002/9781119309376

Hu, Q., Chakhar, S., Siraj, S., & Labib, A. (2017). Spare parts classification in industrial manufacturing using the dominance-based rough set approach. European Journal of Operational Research, 262(3), 1136–1163. https://doi.org/10.1016/j.ejor.2017.04.040

Huang, H., & Siraj, S. (2024a). Correction: Quantifying and reducing the complexity of multi-line charts as a visual aid in multi-criteria decision-making. Annals of Operations Research, 341(2–3), 1351–1351. https://doi.org/10.1007/s10479-024-06121-2

Huang, H., & Siraj, S. (2024b). Quantifying and reducing the complexity of multi-line charts as a visual aid in multi-criteria decision-making. Annals of Operations Research. https://doi.org/10.1007/s10479-024-06090-6

Huang, H., Zhang, X., Corrente, S., Siraj, S., & Kiba-Janiak, M. (2024). Facilitating Sustainable Logistics Policy Development Using Multicriteria Satisfaction Analysis: A Case of Preference Mapping for Cargo Bike Last-Mile Delivery. In Strengthening European Mobility Policy (pp. 129–144). Springer Nature. https://doi.org/10.1007/978-3-031-67936-0_10

Ishizaka, A., Pereira, V., & Siraj, S. (2021). AHPSort-GAIA: a visualisation tool for the sorting of alternative in AHP portrayed through a case in the food and drink industry. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04082-4

Ishizaka, A., & Siraj, S. (2016). AHPSort-GAIA: A Visualisation tool for the sorting of alternatives in AHP. Or58 the or Society Annual Conference, 90–95.

Ishizaka, A., & Siraj, S. (2018). Are multi-criteria decision-making tools useful? An experimental comparative study of three methods. European Journal of Operational Research, 264(2), 462–471. https://doi.org/10.1016/j.ejor.2017.05.041

Ishizaka, A., & Siraj, S. (2020). Interactive consistency correction in the analytic hierarchy process to preserve ranks. Decisions in Economics and Finance, 43(2), 443–464. https://doi.org/10.1007/s10203-020-00309-4

Ishizaka, A., Siraj, S., & Nemery, P. (2016a). Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool. Energy, 95, 602–611. https://doi.org/10.1016/j.energy.2015.12.009

Ishizaka, A., Siraj, S., & Nemery, P. (2016b, August 15). AN EVOLUTIVE DESCRIPTIVE MAPPING VISUALISATIO TOOL WITH THE INTEGRATED GAIA-AHP. https://doi.org/10.13033/isahp.y2016.025

Lundy, M., Siraj, S., & Greco, S. (2017). The mathematical equivalence of the “spanning tree” and row geometric mean preference vectors and its implications for preference analysis. European Journal of Operational Research, 257(1), 197–208. https://doi.org/10.1016/j.ejor.2016.07.042

Naeem, S., & Siraj, S. (2013). A Framework to Select Edge Detection Method using Multi-criteria Decision Making. 730–735. https://doi.org/10.1109/smc.2013.129

Pelegrina, G., & Siraj, S. (2022, September 9). Shapley value-based approaches to explain the robustness of classifiers in machine learning. https://doi.org/10.48550/arxiv.2209.04254

Pelegrina, G., Siraj, S., Duarte, L., & Grabisch, M. (2024). Explaining contributions of features towards unfairness in classifiers: A novel threshold-dependent Shapley value-based approach. Engineering Applications of Artificial Intelligence, 138(B), 109427. https://doi.org/10.1016/j.engappai.2024.109427

Qi, L., Xu, M., & Siraj, S. (2015, July 24). A HADOOP-based data processing platform for fresh agro-products traceability. Http://Www.Iadisportal.Org/Tpmc-2015-Proceedings.

Siraj, S., Barbati, M., & Labib, A. (2015). Learning from Errors in Healthcare. Portsmouth, United Kingdom.

Siraj, S., Keane, J., & Mikhailov, L. (2010). Estimating preferences from pairwise comparisons using multiobjective optimization. Or52 Keynotes and Extended Abstracts 52nd Conference of the Operational Research Society 2010, 138–140.

Siraj, S., Leonelli, R., Keane, J., & Mikhailov, L. (2013). PriEsT: A Tool to Estimate Priorities from Inconsistent Judgments. 44–49. https://doi.org/10.1109/smc.2013.15

Siraj, S., Mikhailov, L., & Keane, J. (2012a). A heuristic method to rectify intransitive judgments in pairwise comparison matrices. European Journal of Operational Research, 216(2), 420–428. https://doi.org/10.1016/j.ejor.2011.07.034

Siraj, S., Mikhailov, L., & Keane, J. (2012b). Corrigendum to “Enumerating all spanning trees for pairwise comparisons” [Comput. Oper. Res. 39 (2012) 191–199]. Computers & Operations Research, 39(9), 2265. https://doi.org/10.1016/j.cor.2011.11.010

Siraj, S., Mikhailov, L., & Keane, J. (2012c). Enumerating all spanning trees for pairwise comparisons. Computers & Operations Research, 39(2), 191–199. https://doi.org/10.1016/j.cor.2011.03.010

Siraj, S., Mikhailov, L., & Keane, J. (2012d). Preference elicitation from inconsistent judgments using multi-objective optimization. European Journal of Operational Research, 220(2), 461–471. https://doi.org/10.1016/j.ejor.2012.01.049

Siraj, S., Mikhailov, L., & Keane, J. (2015a). Contribution of individual judgments toward inconsistency in pairwise comparisons. European Journal of Operational Research, 242(2), 557–567. https://doi.org/10.1016/j.ejor.2014.10.024

Siraj, S., Mikhailov, L., & Keane, J. (2015b). PriEsT: an interactive decision support tool to estimate priorities from pairwise comparison judgments. International Transactions in Operational Research, 22(2), 217–235. https://doi.org/10.1111/itor.12054

Syed, T., Bhatti, Z., Clifft, S., Siraj, S., Pahuja, A., & Nawaz, R. (2025). Strategic Alignment of Big Data Analytics: Leveraging Operational and Market Capabilities for Organisational Performance. British Journal of Management. https://doi.org/10.1111/1467-8551.70014