@article {BenRabia2022,
	title = {Simulation-based analytics: A systematic literature review},
	journal = {Simulation Modelling Practice and Theory},
	volume = {117},
	year = {2022},
	note = {cited By 1},
	abstract = {Over time, Decision Support Systems have helped decision makers solve complex problems through Operational Research and Simulation. Nowadays, data explosion is having a profound effect on the ways in which many sectors operate. This advent of massive data gives rise to new concepts and requires new methods and analysis tools. In this paper, we highlight the role of simulation in Business Analytics. In a framework-based analytics, simulation is a technique that can be incorporated into predictive or prescriptive stage. For that, we have posed research questions to limit results to what give a comprehensive description of models, techniques and architectures used in the hybridization between simulation and business analytics. The presented analyses confirm that simulation remains an indispensable mechanism for adding value to analytics project and the coupling between the two techniques is in its embryonic phase. A conclusion presented prospects and future improvements found during the writing of the research. {\textcopyright} 2022 Elsevier B.V.},
	keywords = {Artificial intelligence, Big data, Business analytics, Competitive intelligence, Data Analytics, Data driven decision, Data-driven decision making, Decision making, Decision support systems, Decisions makings, Model-driven, Model-driven decision making, Predictive analytics, Simulation \& analytic ops, Systematic literature review, What-if Analysis},
	doi = {10.1016/j.simpat.2022.102511},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125647406\&doi=10.1016\%2fj.simpat.2022.102511\&partnerID=40\&md5=b8a2d6f53d7e2a53c6c1e7675770c74b},
	author = {Ben Rabia, M.A. and Bellabdaoui, A.}
}
@conference {Rabia2020,
	title = {Simulation as a decision-making tool in a business analytics environment},
	booktitle = {Proceedings - 2020 5th International Conference on Logistics Operations Management, GOL 2020},
	year = {2020},
	note = {cited By 0},
	abstract = {Nowadays, Business Intelligence (BI) plays a key role in the decision-making chain because of what it offers in terms of data availability, structuring, analysis and presentation in the form of dashboards or Key Performance Indicators (KPI) to assist decision-making. Despite its advantages in terms of historicizing the company{\textquoteright}s activity, traditional BI tools do not allow us to project our business into the future and evaluate the impact of a decision on the entire activity of a company. Given this consideration, What-if analysis positions itself as a data-intensive simulation to examine the impact of a decision. In this article, we intend to highlight the role that simulation techniques can play in prescriptive analysis. Then, we present the different architectures that combine the use of simulation in an analytical environment. Finally, we also provide an idea of the future perspectives and challenges in simulation-based analytics. {\textcopyright} 2020 IEEE.},
	keywords = {Advanced Analytics, Benchmarking, Business analytics, Data availability, Data intensive, Decision making, Decision making tool, Future perspectives, Key performance indicators, Simulation technique, What-if Analysis},
	doi = {10.1109/GOL49479.2020.9314725},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100164050\&doi=10.1109\%2fGOL49479.2020.9314725\&partnerID=40\&md5=03afaf905e87539e719dc12b27acd09d},
	author = {Rabia, M.A.B. and Bellabdaoui, A.}
}
@conference {Annouch2016,
	title = {Split delivery and pickup vehicle routing problem with two-dimensional loading constraints},
	booktitle = {SITA 2016 - 11th International Conference on Intelligent Systems: Theories and Applications},
	year = {2016},
	note = {cited By 0},
	abstract = {In this paper, we address the distribution problem of liquefied petroleum gas (LPG). In particular we are targeting the optimization of pickup and split delivery of gas bottles to a set of customers with loading constraints. The problem combines the loading of a heterogeneous fleet of vehicles through a set of different size racks and then the establishment of divisible deliveries (split delivery: SDVRP). The problem discussed in this paper can be presented as a Multi-depot Two-Loading Split Delivery and Pickup using Heterogeneous fleet of Vehicles with Time Windows vehicle Routing Problem and with Multi-Product (2L-SDP-HVRPTW-MP). After proposing a mathematical formulation for this problem (MILP), we tested our model firstly by a small instances using ILOG CPLEX solver following this by testing and discussing numerical results. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/SITA.2016.7772277},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010366293\&doi=10.1109\%2fSITA.2016.7772277\&partnerID=40\&md5=dcf8e30d18c805be9f705a1c130183cf},
	author = {Annouch, A. and Bellabdaoui, A. and Minkhar, J.}
}
