Mohammad Peyman , Xabier A. Martin , Javier Panadero , Angel A. Juan
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引用次数: 0
Abstract
This paper addresses a rich variant of the team orienteering problem under uncertainty to improve urban mobility. Specifically, we conduct a case study using real-world data from urban transportation hubs in Barcelona, gathered from Open Data Barcelona. The study involves routing autonomous delivery drones operating within a university campus to deliver items to designated drop-off points. Traditional optimization techniques often fail to account for the stochastic fluctuations inherent in urban traffic and the complex interactions between various transportation activities. To address these challenges, this research employs a simheuristic framework that combines heuristic optimization with commercial simulation software to replicate the dynamic and uncertain nature of urban environments accurately. The efficiency and practical applicability of our simheuristic framework are demonstrated through comprehensive computational experiments in a real-world context.
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
• methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.;
• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.