agent based simulation

This study aims to explore and assess situations in international markets. In this context, the primary objective is to pinpoint the factors influencing the gas market and to analyze the internal dynamics of each of these factors. Subsequently, based on the factor-driven model of the recognized elements, the interplay and behaviors of these elements as parts of a factor-driven model are investigated.

This research employs the problem structuring approach, also known as soft operational research, specifically the Graph Model for Conflict Resolution (GMCR) method. Additionally, in the quantitative part of this research, factor-based modeling is utilized. In this research, an attempt is first made to obtain a proper understanding of the reality of the gas market, and then a model is built based on this understanding. By identifying the key and leverage parts of the factor-based model and then simulating it for the long term, possible scenarios or states are extracted.

In the first step, key players in the gas market, including the United States, the European Union, Russia, China, India, Iran, Qatar, and the Renewable Energy Group, were identified, and the conflicts between them were modeled. The GMCR analysis resulted in the identification of 28 equilibrium points, which were subsequently clustered into five distinct scenarios. In the next step, an agent-based simulation model was developed based on these scenarios.

Originality/Value: 

By integrating GMCR and Agent-Based Model (ABM), this study has successfully addressed aspects of strategic conflict, market dynamics, and the gradual learning of participants, which were previously overlooked in most earlier research.

High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this end, we seek ways of accelerating the patient flow in order to save time and cost in healthcare facilities.

In this study, we use agent-based simulation to simulate patient care in the operating room. After performing the required validations, a number of improvement scenarios were developed and evaluated.

A hybrid scenario including modifications to the referral time of the patient by the surgeon, transfer time of the surgical set and supplies to the operating room, and the timing of anesthesia proved to have the most positive impact on the criteria i.e. activities, reducing the average Length of Stay (LOS) by 9.69 minutes. The second-most effective scenario involved modifying the referral time of the patient by the surgeon, reduced the LOS by 7.31 minutes.

Originality/Value:

 Through this research, it became apparent that minimizing the patients' LOS improves the efficiency of the operating room as it helps reduce the overall idle time and increases the number of operations carried out in each shift. Making time even for one additional operation per day significantly increases the operating room income. Moreover, a shorter LOS means less fatigue for the medical staff and reduces the total cost of running the operating room by reducing the staff's overtime hours.