Simulation Modelling Practice and Theory

The yaml version of the seven DEVSimPy models associated with the WSpyc DEVS models library. They require the version 4.0 of DEVSimPy (available from \url{https://github.com/capocchi/DEVSimPy/tree/version-4.0}) and they can be simulated after having both imported the WSpyc directory as a library and the activity\_tracking.pyc plugins. The archive contains a video dedicated to guide the user in installing and simulating the models.

Data and Figures (excluding maps) associated with the article: Population Downscaling in Multi-Agent Urban Traffic Simulations: A Comprehensive Review and Case Study

AnyLogic University 8.4.0 model developed for the test case of the manuscript. Each proposed procedure of the method was implemented as a custom experiment in Java language.

This contains MATLAB Files used for simulation and the code corresponding to the proposed model It also contains the code for the routing details. more details and comments to be added later.

SIMAN code of the simulation model

Data of the problem instances in section 3.5.

This repository is part of the Ph.D. thesis of Irene S. van Droffelaar, Delft University of Technology. This repository accompanies the paper "Simulation-optimization configurations for real-time decision-making in fugitive interception" (https://doi.org/10.1016/j.simpat.2024.102923). The optimization algorithm can be found under platypus-fork.zip. In simopt-configs.zip, the folders _cleaned data_ and _models_ contain all results and software for:- Sequential Simulation Optimization (abbreviated as _seq_ in file names), solved with MIP solver CBC (https://github.com/coin-or/Cbc)- Sequential Simulation Optimization (_seq_), solved with metaheuristic Borg- Simulation Model Optimization (abbreviated as _smo_ in file names), solved with metaheuristic Borg

This repository is part of the Ph.D. thesis of Irene S. van Droffelaar, Delft University of Technology. This repository accompanies the paper "Simulation-optimization configurations for real-time decision-making in fugitive interception" (https://doi.org/10.1016/j.simpat.2024.102923). The optimization algorithm can be found under platypus-fork.zip. In simopt-configs.zip, the folders _cleaned data_ and _models_ contain all results and software for:- Sequential Simulation Optimization (abbreviated as _seq_ in file names), solved with MIP solver CBC (https://github.com/coin-or/Cbc)- Sequential Simulation Optimization (_seq_), solved with metaheuristic Borg- Simulation Model Optimization (abbreviated as _smo_ in file names), solved with metaheuristic Borg

Simulation data in AnyLogic software

These are the datasets used in the following study: Fachada, N., Lopes, V.V., Martins, R.C. and Rosa, A.C., Model-independent comparison of simulation output. Simulation Modelling Practice and Theory, 72:131–149, 2017, http://dx.doi.org/10.1016/j.simpat.2016.12.013 (arXiv version available at http://arxiv.org/abs/1509.09174)