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The Influence of Communication Strategies of Intelligent Agents in Production Systems on the Shift of Sustainable Solutions

Author

Listed:
  • Polina A. Sharko

    (Laboratory of Digital Modeling of Industrial Systems, Peter the Great St. Petersburg Polytechnic University, St Petersburg 195251, Russia)

  • Zhanna V. Burlutskaya

    (Laboratory of Digital Modeling of Industrial Systems, Peter the Great St. Petersburg Polytechnic University, St Petersburg 195251, Russia)

  • Aleksei M. Gintciak

    (Laboratory of Digital Modeling of Industrial Systems, Peter the Great St. Petersburg Polytechnic University, St Petersburg 195251, Russia)

  • Salbek M. Beketov

    (Laboratory of Digital Modeling of Industrial Systems, Peter the Great St. Petersburg Polytechnic University, St Petersburg 195251, Russia)

  • Karina A. Lundaeva

    (Laboratory of Digital Modeling of Industrial Systems, Peter the Great St. Petersburg Polytechnic University, St Petersburg 195251, Russia)

Abstract

Current decision support systems for recommending labor resource allocation and generating production schedules in the systems with decentralized technological process control often fail to account for the impact of participants’ communication strategies on the shifts in target performance indicators, which depend on the alignment between local goals of production units and the global objectives of the system. The goal of the present study is to develop an approach for determining optimal communication parameters among intelligent agents to achieve system-level performance targets using the previously developed multiagent systems (MAS) for optimizing technological processes. The research investigates how agent constraint systems influence both overall system welfare and the individual welfare of agents, considering the shifts in their objective functions driven by preferred communication strategies. A workflow is developed to identify effective constraints. Using this workflow, the study provides recommendations for assigning regional field development plans, accounting for participants’ tendencies toward cooperation. On data where the potential for increasing the region’s flow rate through optimization of labor resource allocation and scheduling of well intervention operations (GTO) does not exceed 6%, the presented solution enabled the development of field plans that result in an additional 1% increase in the predicted oil production region’s flow rate on top of the gain achieved through resource allocation optimization.

Suggested Citation

  • Polina A. Sharko & Zhanna V. Burlutskaya & Aleksei M. Gintciak & Salbek M. Beketov & Karina A. Lundaeva, 2025. "The Influence of Communication Strategies of Intelligent Agents in Production Systems on the Shift of Sustainable Solutions," Sustainability, MDPI, vol. 17(24), pages 1-13, December.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:24:p:11130-:d:1816192
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