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ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 2. Vol. 30. 2024
DOI: 10.17587/it.30.91-102
N. S. Samedov, Graduate Student,
Derzhavin Tambov State University, Tambov, Russian Federation
Review and Analysis of City Strategic Management Systems
Strategic city management systems serve for information and analytical support of decision makers. Models of urban systems based on the agent-based approach and system dynamics are highly accurate, allow real-time monitoring of the urban environment, timely preparation for possible emergencies, and also choose the best ways to develop the city's infrastructure. Research in this area is very relevant today: dozens of models have been proposed that describe almost all urban processes. However, the question of systematization of these models remains open. In this paper, an overview of the existing city management systems implemented using the methods of system dynamics and the agent approach is made. The description of the latest researches of foreign authors in the field of agent-based modeling is given.
Keywords: city management algorithms, dynamic systems, simulation modeling, forecasting, multi-agent approach, city strategic management systems
P. 91-102
References
- Map of the real population density of Moscow: [Web], available at: https://andreygeo.livejournal.com/4430.html (accessed: 30.03.2023).
- Ageeva A. F. Simulation modeling of the dynamics of urban systems using the agent-based approach, Science journal "Elektronnye informatsionnye sistemy", 2020, no. 3 (26), pp. 37—53 (in Russian).
- Katalevskii D. Yu. Fundamentals of simulation modeling and system analysis in management, Moscow, Publishing House "Delo" RANKhiGS, 2015, pp. 496 (in Russian).
- Karpov Yu. G. Simulation modeling of systems. Introduction to Simulation with Anylogic 5, St. Petersburg, BKhV — Petersburg, 2009 (in Russian).
- Fattakhov M. R. Agent-oriented model of socio-economic development of megacities (on the example of Moscow): abstract of the dissertation of a candidate of economic sciences, Moscow, 2011, šš. 30 (in Russian).
- Makarov V. L., Bakhtizin A. R., Beklaryan G. L., Akopov A. S. Simulation of the smart city system: concept, methods and examples, Natsionalnye interesy: prioritety i bezopasnost, 2019, no. 2 (371) (in Russian).
- Kopyrin A. S., Burunin O. A. Simulation of the market of utilization of solid household waste of a resort city, Vestnik Altaiskoi akademii ekonomiki i prava, 2019, no. 1-1, pp. 70—76 (in Russian).
- Galperova E. V., Galperov V. I., Loktionov V. I., Makagonova N. N. Application of intelligent methods to model the impact of new factors in the development of the energy sector on the demand for electricity, Informatsionnye i matematicheskie tekhnologii v nauke i upravlenii, 2019, no. 1 (13) (in Russian).
- Zhang Q., Hu T., Zeng X., Yang P., Wang X. Exploring the effects of physical and social networks on urban water system's supply-demand dynamics through a hybrid agent-based modeling framework, Journal of Hydrology, 2023, vol. 617: 129108.
- Arasteh M. A., Farjami Y. New hydro-economic system dynamics and agent-based modeling for sustainable urban ground-water management: A case study of Dehno, Yazd Province, Iran, Sustainable Cities and Society, 2023, vol. 72: 103078.
- Darbandsari P., Kerachian R., Malakpour-Estalaki S., Khorasani H. An agent-based conflict resolution model for urban water resources management, Sustainable Cities and Society, 2020, vol. 57:102112.
- Bolton E. R., Berglund E. Z. Agent-based modeling to assess decentralized water systems: Micro-trading rainwater for aquifer recharge, Journal of Hydrology, 2023, vol. 618: 129151.
- Moradikian S., Emami-Skardi M. J., Kerachian R. A distributed constraint multi-agent model for water and reclaimed wastewater allocation in urban areas: Application of a modified ADOPT algorithm, Journal of Environmental Management, 2022, vol. 317:115446.
- Zhang Z., Tian W., Liao Z. Towards coordinated and robust real-time control: a decentralized approach for combined sewer overflow and urban flooding reduction based on multi-agent reinforcement learning, Water Research, 2023, vol. 229:119498.
- Ding Z., Liu R., Wang Y., Tam V. WY., Ma M. An agent-based model approach for urban demolition waste quantification and a management framework for stakeholders, Journal of Cleaner Production, 2021, vol. 285: 124897.
- Peng Z., Lu W., Webster C. Understanding the effects of a construction waste cap-and-trade scheme: An agent-based modeling study in Hong Kong, Journal of Cleaner Production, 2022, vol. 375: 134135.
- Zhu C., Fan R., Luo M., Lin J., Zhang Y. Urban food waste management with multi-agent participation: A combination of evolutionary game and system dynamics approach, Journal of Cleaner Production, 2020, Vol. 275: 123937.
- Casavola A., Franze G., Gagliardi G., Tedesco F. A Multi-Agent Trust and Reputation Mechanisms for the Management of Smart Urban Lighting Systems, IFAC-PapersOnLine, 2022, vol. 55, iss. 6, pp. 545—550.
- Yue T., Long R., Chen H., Liu J., Liu H., Gu Y. Energy-saving behavior of urban residents in China: A multi-agent simulation, Journal of Cleaner Production, 2020, vol. 252:119623.
- Volpe R., Catrini P., Piacentino A., Fichera A. An agent-based model to support the preliminary design and operation of heating and power grids with cogeneration units and photovoltaic panels in densely populated areas, Energy, 2022, vol. 261: 125317. Part B.
- Yi Z., Chen B., Liu X. C., Wei R., Chen J., Chen Z. An agent-based modeling approach for public charging demand estimation and charging station location optimization at urban scale, Computers, Environment and Urban Systems, 2023, vol. 101: 101949.
- Wolbertus R., van den Hoed R., Kroesen M., Chorus C. Charging infrastructure roll-out strategies for large scale introduction of electric vehicles in urban areas: An agent-based simulation study, Transportation Research Part A: Policy and Practice, 2021, vol. 148, pp. 262-285.
- Kalahasthi L. K., Sanchez-Diaz I., Castrellon J. P., Gil J., Browne M., Hayes S., Ros C. S. Joint modeling of arrivals and parking durations for freight loading zones: Potential applications to improving urban logistics, Transportation Research Part A: Policy and Practice, 2022, vol. 166, pp. 307—329.
- Gatta V., Marcucci E., Le Pira M., Inturri G., Ignac-colo M., Pluchino A. E-groceries and urban freight: Investigating purchasing habits, peer influence and behaviour change via a discrete choice/agent-based modelling approach, Transportation Research Procedia, 2020, vol. 46v pp. 133—140.
- Firdausiyah N., Taniguchi E., Qureshi A. G. Multi-agent simulation-Adaptive dynamic programming-based reinforcement learning for evaluating joint delivery systems in relation to the different locations of urban consolidation centres, Transportation Research Procedia, 2020, vol. 46, pp. 125—132.
- Calabro G., Le Pira M., Giuffrida N., Fazio M., Inturri G., Ignaccolo M. Modelling the dynamics of fragmented vs. consolidated last-mile e-commerce deliveries via an agent-based model, Transportation Research Procedia, 2022, vol. 62, pp. 155—162.
- Kubler J., Reiffer A., Briem L., Vortisch P. Integrating Neighbours into an Agent-Based Travel Demand Model to Analyse Success Rates of Parcel Deliveries, Procedia Computer Science, 2022, vol. 201, pp. 181—188.
- Jelen G., Babic J., Podobnik V. A multi-agent system for context-aware electric vehicle fleet routing: A step towards more sustainable urban operations, Journal of Cleaner Production, 2022, vol. 374: 134047.
- Wilson A. M., Romero-Lankao P., Zimny-Schmitt D., Sperling J., Young S. Linking transportation agent-based model (ABM) outputs with micro-urban social types (MUSTs) via typology transfer for improved community relevance, Transportation Research Interdisciplinary Perspectives, 2023, vol. 17: 100748.
- Qin W., Sun Y. N., Zhuang Z. L., Lu Z. Y., Zhou Y. M. Multi-agent reinforcement learning-based dynamic task assignment for vehicles in urban transportation system, International Journal of Production Economics, 2021, vol. 240: 108251.
- Calabro G., Le Pira M., Giuffrida N., Inturri G., Ignaccolo M., de A. Correia G. H. Designing demand responsive transport services in small-sized cities using an agent-based model, Transportation Research Procedia, 2023, vol. 69, pp. 759—766.
- Wang S., de Almeida Correia G. H., Lin H. X. Modeling the competition between multiple Automated Mobility on-Demand operators: An agent-based approach, Physica A: Statistical Mechanics and its Applications, 2022, vol. 605: 128033.
- Palanca J., Terrasa A., Rodriguez S., Carrascosa C., Julian V. An agent-based simulation framework for the study of urban delivery, Neurocomputing, 2021, vol. 423, pp. 679—688.
- Tian S., Li Y., Zhang X., Zheng L., Cheng L., She W., Xie W. Fast UAV path planning in urban environments based on three-step experience buffer sampling DDPG, Digital Communications and Networks, 2023.
- Du W., Guo T., Chen J., Li B., Zhu G., Cao X. Cooperative pursuit of unauthorized UAVs in urban airspace via multi-agent reinforcement learning, Transportation Research Part C: Emerging Technologies, 2021, vol. 128: 103122.
- Jin J., Ji Q. Agent-based Deep Urban Traffic Recommender, IFAC-PapersOnLine, 2020, vol. 53, iss. 5, pp. 588—591.
- Wang H., Shi W., He W., Xue H., Zeng W. Simulation of urban transport carbon dioxide emission reduction environment economic policy in China: An integrated approach using agent-based modelling and system dynamics, Journal of Cleaner Production, 2023, vol. 392: 136221.
- Shin H., Bithell M. TRAPSim: An agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul, Computers, Environment and Urban Systems, 2023, v ol. 99: 101894.
- Maggi E., Vallino E. Price-based and motivation-based policies for sustainable urban commuting: An agent-based model, Research in Transportation Business & Management, 2021, vol. 39:100588.
- Bin Othman N., Jayaraman V., Chan W., Kenneth Loh Z. X., Rajendram R., Mepparambath R. M., Agrawal P., Ramli M. A., Qin Z. SUMMIT: A multi-modal agent-based co-simulation of urban public transport with applications in contingency planning, Simulation Modelling Practice and Theory, 2023, vol. 126:102760.
- Zhao B., Tang Y., Wang C., Zhang S., Soga K. Evaluating the flooding level impacts on urban metro networks and travel demand: behavioral analyses, agent-based simulation, and large-scale case study, Resilient Cities and Structures, 2022, vol 1, iss. 3, pp. 12—23.
- Pan Z., Wei Q., Wang H. Agent-based simulation of hindering effect of small group behavior on elevated interval evacuation time along urban rail transit, Travel Behaviour and Society, 2021, vol. 22, pp. 262—273.
- Nickdoost N., Jalloul H., Choi J. An integrated framework for temporary disaster debris management sites selection and debris collection logistics planning using geographic information systems and agent-based modeling, International Journal of Disaster Risk Reduction, 2022, vol. 80: 103215.
- Gong Y., Dai M., Gu F. CARESim: An integrated agent-based simulation environment for crime analysis and risk evaluation (CARE), Expert Systems with Applications, 2023, vol. 214: 119070.
- Roses R., Kadar C., Malleson N. A data-driven agent-based simulation to predict crime patterns in an urban environment, Computers, Environment and Urban Systems, 2021, vol. 89: 101660.
- Zhu H., Wang F. An agent-based model for simulating urban crime with improved daily routines, Computers, Environment and Urban Systems, 2021, Vol. 89:101680.
- Joubert C. J., Saprykin A., Chokani N., Abhari R. S. Large-scale agent-based modelling of street robbery using graphical processing units and reinforcement learning, Computers, Environment and Urban Systems, 2022, vol. 94: 101757.
- Shan S. N., Zhang Z. C., Ji W. Y., Wang H. Analysis of collaborative urban public crisis governance in complex system: A multi-agent stochastic evolutionary game approach, Sustainable Cities and Society, 2023, vol. 91: 104418.
- Gonzalez-Mendez M., Olaya C., Fasolino I., Grimaldi M., Obregon N. Agent-Based Modeling for Urban Development Planning based on Human Needs. Conceptual Basis and Model Formulation, Land Use Policy, 2021, vol. 101:105110.
- Cao Y., Li F., Xi X., Corne van Bilsen D. J., Xu L. Urban livability: Agent-based simulation, assessment, and interpretation for the case of Futian District, Shenzhen, Journal of Cleaner Production, 2021, vol. 320:128662.
- Yildiz B., Cay das G. Fuzzy logic in agent-based modeling of user movement in urban space: Definition and application to a case study of a square, Building and Environment, 2020, vol. 169:106597.
- Caprioli C., Bottero M., De Angelis E. Combining an agent-based model, hedonic pricing and multicriteria analysis to model green gentrification dynamics, Computers, Environment and Urban Systems, 2023, vol. 102:101955.
- Sun S., Parker D. C., Brown D. G. From an agent-based laboratory to the real world: Effects of "neighborhood" size on urban sprawl, Computers, Environment and Urban Systems, 2023, vol. 99: 101889.
- Chen Y., Chen Z., Guo D., Zhao Z. Simulating spatio-temporal dynamics of urban underground space development using multi-agent system: A case study in Changzhou City, China, Tunnelling and Underground Space Technology, 2022, vol. 124:104482.
- Zhang C., Zhao Z., Guo D., Gong D., Chen Y. Optimization of spatial layouts for deep underground infrastructure in central business districts based on a multi-agent system model, Tunnelling and Underground Space Technology, 2023, vol. 135:105046.
- Hu W., Dong J., Yuan J., Ren R., Chen Z., Cheng H. Agent-based modeling approach for evaluating underground logistics system benefits and long-term development in megacities, Journal of Management Science and Engineering, 2022, vol. 7, iss. 2, pp. 266—286.
- Wang A., Wang H., Chan E. H. W. The incompatibility in urban green space provision: An agent-based comparative study, Journal of Cleaner Production, 2020, vol. 253: 120007.
- Chen W., Zhao L., Kang Q., Di F. Systematizing heterogeneous expert knowledge, scenarios and goals via a goal-reasoning artificial intelligence agent for democratic urban land use planning, Cities, 2020, vol. 101: 102703.
- Picascia S., Mitchell R. Social integration as a determinant of inequalities in green space usage: Insights from a theoretical agent-based model, Health & Place, 2022, vol. 73: 102729.
- Liang X., Lu T., Yishake G. How to promote residents' use of green space: An empirically grounded agent-based modeling approach, Urban Forestry & Urban Greening, 2022, vol. 67: 127435.
- 61. Jiang X., Li B., Zhao H., Zhang Q., Song X., Zhang H. Examining the spatial simulation and land-use reorganisation mechanism of agricultural suburban settlements using a cellular-automata and agent-based model: Six settlements in China, Land Use Policy, 2022, vol. 120:106304.
- Said Hassen F., Kalla M., Dridi H. Using agent-based model and Game Theory to monitor and curb informal houses: A case study of Hassi Bahbah city in Algeria, Cities, 2022, vol. 125: 103617.
- Zakrajsek F. J., Vodeb V. Agent-based geographical modeling of public library locations, Library & Information Science Research, 2020. vol. 42, iss. 2: 101013.
- Data Assimilation for Agent-Based Modelling (DUST): Website for the DUST research project: [Web] / University of Leeds. Cop., 2020, available at: https://dust.leeds.ac.uk/ (accessed: 10.04.2023).
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