agent-based simulation

Uncertainty in food supply in the country has heightened the focus on the supply chain of semi-prepared foods. Like many economic sectors, the food supply chain has not been immune to the impacts of the COVID-19 pandemic. Food supply, influenced by the behaviors of governments and customers during such crises, can exacerbate uncertainties in the supply chain, underlining the need for simulating the behavior of supply chain actors. Accordingly, the aim of this study is to develop an agent-based simulation to analyze the relationships between actors in the supply chain of ready and semi-prepared foods concerning raw material imports and final product exports during the COVID-19 pandemic.

This study is applied in its aim and descriptive-analytical in terms of data collection, utilizing agent-based simulation techniques. The case study for simulating pandemic conditions in the supply chain is one of the ready and semi-prepared food companies in Tehran Province with a production capacity of 216,000 tons per month. To identify factors, variables, and parameters for the agent-based model, the research employed thematic analysis, reviewing prior studies, and conducting interviews with 20 industry experts from the ready and semi-prepared food sector and supply chain experts from Amadeh-Laziz Company.

The findings identified three main actors in the food supply chain that play a role in exports: “Government”  (e.g., customs, national standards organization, consumer protection organizations, industry and mining banks, Iran Chamber of Commerce-Industries-Mines and Agriculture, and the Food and Drug Administration), “Supply Chain Companies” (e.g., domestic suppliers, foreign suppliers, manufacturers, and distributors), and “Final Customers” (e.g., domestic and foreign customers). The key uncertainty identified in interviews was governmental intervention or non-intervention in exports and imports.Accordingly, two scenarios were developed: “Governmental intervention in exports and imports”, and “Lack of governmental support in exports and imports during the pandemic”. These scenarios were analyzed using agent-based simulation to examine the relationships, characteristics, and decision-making behaviors of supply chain actors. Additionally, fuzzy DEMATEL was used as a complementary method to identify the most significant relationships among actors in the ready and semi-prepared food supply chain. Simulation parameters included: Import tariffs on raw materials (%), Export tariffs on final products (%), Total monthly domestic demand (in thousand tons), Total monthly foreign demand (in thousand tons), Total monthly demand (in thousand tons), Maximum production capacity (in thousand tons).Simulation variables included: Percentage change in total costs compared to the base price, Percentage of completed domestic customer orders, Percentage of completed foreign customer orders, Total completed orders (total sales volume), Profits from the domestic market, Profits from the foreign market, Percentage of overall profitability. The simulation was performed under the two scenarios of governmental non-intervention and governmental intervention in importing raw materials and exporting final products, with emphasis on two main variables: profitability and order fulfillment rate, which encapsulate the model’s overall outcomes.

The results indicate that under the governmental intervention scenario, profitability increased by 6%, and total order fulfillment improved by 14%. Based on the defined criteria for scenario comparison, the second scenario (governmental support) provides more favorable conditions for supporting domestic production, enhancing employment levels, and ensuring food security in both domestic and international markets.

This paper has investigated the inventory and financial flows in supply chains. Its purpose is to provide a method to optimize these two flows for chain members, where Return on Capital (ROC) is defined as the dependent variable, and cash conversion cycle (CCC) equation components, which show financial and physical flows, are formulated as independent variables. The data of chain members from six selected industries, including auto & parts, pharmacy, food, petrochemical, metal, and mining, have been extracted. Two scenarios, 1) revision of independent variables without a change in the cash conversion cycle of the entire supply chain, and 2) reducing the days of independent variables along with reducing the cash conversion cycle, have been defined. The problem is simulated using Agent-Based Modeling and NetLego software. Results of the first scenario indicate that if Days Inventory Outstanding (DIO) is reduced in downstream and transferred to upstream of the chain, and Days Payment Outstanding (DPO) in the upstream is shortened, ROC is improved for the entire chain. Also, the results of the second scenario show that, in proportion to the reduction of the cash conversion cycle through productivity under collaboration of chain members, the performance improvement of ROC is remarkable.

One of the approaches used by companies to gain competitive advantage in today's uncertain and competitive environment is supply chain management. The strategic aspect of the supply chain has made it more important to identify and evaluate the risks of the chain. Despite the increasing attention paid to supply chain risk management by users and academics, little research has been done on assessing supply chain risks in the field of service. Given the substantial differences in product and service supply chain models, this study, while introducing the role of the insurance industry's supply chain players, seeks to identify and evaluate the risks of the chain with a basic agent simulation approach.In this study, based on the Service Lens Based Factor Survey method, according to insurance experts, factors and risks of the insurance industry supply chain were identified using parameters extracted from statistical reports and financial statements and The probability and magnitude of the effects of each of the identified risks in both normal and critical situations, two performance indicators of the insurance companies, namely profit and loss ratio for the three selected companies, during 1393-1408 Simulated on Netlogo software environment. By testing, executing and analyzing the results of multiple simulation times, he results of the study, show the extent of change in the profit and loss parameters in relation to the insurance industry's supply chain risks, under normal and critical conditions over different years

The development of the Internet of Things can be used to empower and improve the quality of human life, especially for the disabled. In this regard, the use of Internet of Things services in the field of rehabilitation requires the new Internet of Things businesses; Therefore, it is necessary to determine competitive and cooperation strategies in completing the product chain for the development and evolution of new businesses. The key issue is how to analyze the components of the business ecosystem and evaluate the role and behavior of actors who interact with each other to achieve co-evolution. This research aims to provide an analytical model for the development of the business ecosystem of the Internet of Things and to analyze the interactions and behaviors of its actors. According to the complexity and uncertainty of the mentioned ecosystem, a model based on the agent-based approach in the technology management system was proposed, and in the following, the simulation and analysis of the said model to network businesses based on the layers of the Internet of Things architecture and actors' interactions in Economic, technological, social and legal environments took place. The findings indicated a change in the behavior of associations, partners, government, and stakeholders in different roles and their influence on each other; Therefore, based on the analysis of the behavior of the agents, it led to the determination of the contribution and role of the actors in the direction of the evolution of the ecosystem. The findings of the present research can help policymakers and executive managers to improve the development strategy of the Internet of Things business to provide the services needed by the disabled.

One of the most important factors in understanding customer behavior is identifying their expectations. Therefore, this study in order to design customer expectations model for platform with agent-based model approach. At first, for finding customers and servants expectations was used of semi-structure interview and then was done automatic clustering with using meta-heuristic algorithms in order to find different factors. Then, with the factor-based simulation approach, the model was designed in Any Logic software. After designing the model, using design method of Taguchi experiments (Qualitek-4 software), scenarios for the growth and development of the platform based on effective factors (liquidity the quality of communication and trust) designed on four levels and finally simulation was performed and scenarios were examined in the simulation environment. the research results showed that the appropriate level of platform growth and development indicators in the fourth level of liquidity, the fourth level of communication quality and the fourth level of trust. In addition, after implementing the optimal scenario in the simulation environment was determined that the percentage of value created on the Instagram platform due to the implementation of the desired scenario is equal to 0.934.

The increasing concern about the deteriorating effects of supply chains related activities on the environment has led to the growing attention to develop green closed-loop supply chains in order to minimize greenhouse gases emission. This paper presents a green closed-loop supply chain model developed under the demand uncertainty aiming at minimizing total cost and total CO2 emission across the supply chain, and maximizing the product’s market share in the presence of a competitor. In this regards, an agent-based market model is developed to estimate the demand’s parameter function then a hybrid simulation model which integrates agent-based and discrete event simulation modelling approaches is designed to simulate the closed-loop supply chain which is the novelty of this paper. Then, scenarios are created using Taguchi design of experiments (DOE) method, and are executed with the market model and the supply chain model to capture total cost, total CO2 and market share. A decision matrix is configured using scenarios and recorded results for three mentioned criteria and ELECTRE and SAW methods are used to rank scenarios and select the best one. The other contribution of this research is its comprehensiveness in considering variables related to three categories of inventory replenishment policy, marketing mix (price and advertisement) and transportation. An automotive industry case is provided to demonstrate the capabilities of the model and its applicability and effectiveness in resolving real-world problems.

One of the most important challenges of supply chains is the coordination of inventory policies among supply chain elements including suppliers, manufacturers, and distributors. Accordingly, the current study aims to investigate the achievement of the elements of the petrol distribution system to the optimal level of inventory. At first, the supply network of National Guilan Oil Products Distribution Company is defined as a complex adaptive system and then, this network is simulated using agent-based modeling. The core component of this simulation consists of interactions between agents or members of the supply network in the context of inventory management based on the economic order quantity (EOQ). The results of simulation in Net Logo software showed that agent-based modeling of the network in the form of a complex adaptive system leads to better understanding of the behavior of supply chain agents in their achievement to the optimal inventory level and enables them to get the proper estimate of the economic order quantity, re-order point and total cost. In summary, it can be seen that the agents in the supply chain have the ability to provide their customers’ needs and will not face lost sales as long as they do not pay extra inventory costs.

Recently, the importance of the service sector is rapidly increasing affected by the global economic development in developed countries and even emerging economies, which is introduced as "service economy" in some literature. However, from a scientific standpoint, the concepts of purchase and supply are still rooted in production area. In spite of growing interest in the theme of service and service supply chain management, there is still no acceptable and comprehensive definition for it. The aim of this study is to identify banking service supply chain in Iran and simulating it based on the implementation of Agent Based approach. In this paper, by means of Netlogo software an Agent-Based Framework was developed for Service Supply Chain Configuration in the banking industry for five Iranian private banks with the market share of 32.4 percent during 2017-2025 in the. What the model does is to track the relevant important parameters associated with the agents of customer, bank, central bank, other banks and banks companies during the mentioned years. The results of the research have been reported in two sections including the simulation of the most important output variables in five banks based on the separated results and comparing the results during the mentioned time period as well as simulating the implementation of two specific scenarios.

Considering the development of services in global economy, redefinition of supply chain management in this context is necessary because the concept of supply chain management cannot be applied to service-oriented businesses. Therefore, this paper aims to identify the banking service supply chain and perform an agent-based simulation using a service dominant logic approach; this is important due to the necessity of developing an applicable model for supply chain management of banking services. This supply chain model is processed through agent-based simulation in Netlogo for 5 banks in privatized and private sectors during 1388-1404, where market share is 32.4%. This model considers the flow of profit and other important parameters related to the customers, the bank, the central bank, and other banks and corporations during the mentioned period. The results of the experiments and analyses in multiple simulation times indicated the variations and changes of the important parameters associated with above-mentioned factors during these years.