Agent based Modeling in Supply Chain

The agent based modeling is the concept in which the members involved in the supply chain activities and coordinate the activities of movement of goods and information. These movements of information are recognized to make the efforts more collaboratively to achieve higher quality of supply chain management globally.   

A computational method gives the exploration to researcher to create, experiment, analyze with the composition of flow of interaction in the environment. A conceptual implementation is recognized in the purpose of supply chain management.  (Zhu, 2008)

The information sharing with the team members about the supply of goods and services to ensures the process of supply chain.  The information flow of interactions with the sophisticated   modeling pattern realizes the agent based modeling importance in the supply chain system. The assessment of information sharing in the supply chain also identified by agent based modeling. In the negotiation, the manufacturer and suppliers come with agreement with the capacity utilization. This means both the parties negotiate on the quantity supplied with the market demand need for the early replenishment of inventory. (Zhu, 2008)

The basic purpose of agent based modeling is the understanding of individuals behaviors in the organization and how they support the information with thither team members.  This is suitable for the social sciences reflection.  The organizational behaviors as well as employee productivity is gauge through the agent based modeling.

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Use of agent based modeling in supply chain:

The flow of interaction like the one information, material movement, personnel, money, capital and orders are effectively utilize through the agent based modeling in the supply chain activities. The cooperation, negotiation and coordination are the interaction examples used in the supply chain process for the service quality improvement.  In the cooperation, the members in the supply chain are diverting to one common goal like reduction in lead-time efficiency and minimize inventory cost. In the coordination, the problem solving techniques are analyzed and avoid harmful interactions and get beneficial interactions like transportation timing in delivering raw material to production system. (Zhu, 2008)

The interactions must be taken place form the sides, supplier and manufacturer to improve the performance of supply chain system.  The organizational behavior and human capital are the most important element in the supply chain that confront them by the agent based modeling. It provides powerful and flexible instrument to gain the numerical analysis of the supply chain performance.

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 The improvement in the suppliers quality management is gained through the agent based modeling. The interactions between the employees in the organizational behaviors show the leading performance characteristics of the supply chain system.  One of the major identification of Supply chain performance improvement is gained through meeting the customer expectations regarding services and cost advantage. This reveals that many of the companies exposed agent based modeling in the supply chain to recognize the efficiency in the supply chain system. (Zhu, 2008)

 The Supply chain risk management is the techniques used for the identification of probability of risk occurrences in the supply chain process.  The business continuity plans are also discussed in the Supply chain risk management to get early resilience in the supply chain operations. The agent based modeling and simulation are highly appropriate for the identification of risk structure in the organization. (Mele, Guillén-Gosálbez, Espuna, & Puigjaner, 2007)

 The collaborative planning process is gained through the agent based modeling. The effective interactions as well as coordination between the supply chain process give efficient results in the globally supply chain. The collaboratively operational planning, supply chain management, distribution, and supply chain networks are the major benefits realized from agent based modeling. (Hernández, Alemany, Lario, & Poler, 2009)

Steps involved in agent based modeling of supply chain:

Step 1: In the first step, the properties are idealized and simplified in the system under considerations that means stylized facts.  The experimental data as well observation are reproduced in this step.  The data are evaluated and observed that are according to the requirements and needed to be reproduced.

Step 2: In the second step, simulation purpose is described to derive the predictions, phenomenon, and accurate description. The formulation of scientific puzzle as well as system behavior is also determined under this step.  In the simulation, alternative solutions are described for the purpose of detailed analysis of data predictions and its forecasting.

Step 3: In the third step, agent model is identified. The mathematical analyses are jointly behaved in one entity. The agent model is identified for the execution of mathematical analysis.  The mutually coupled agents jointly work and collaboration the activities of operations.  This gives the jointly effort of agents in presenting the data experimentations in the system accordance.

Step 4: After specifying the agents, the process and mechanism derives system behavior that needed to be discussed.  The empirical evidence is justified in which agent based model is based.  The multi agent simulation is underlying after the specifying mechanism justification.  The empirical evidence is the justification of mechanism that gives the desired outcome.

Step 5: In the last step, the simulation of computer gives empirical evidence of which the features are correctly reproduced in the first step. This shows that carefully constructing agent based modeling in the environment selection gives empirical evidences for the formulation of business activities.  (Helbing & Balietti, 2012)

Explanation of agent based modeling:

The agent based modeling in the simulation is that used for suppliers and manufacturers. The artificial intelligence is the concept derives from the simulation that gives the development of information technologies.  The data of simulation comes from computational experiments that are controlled.  The agent based model simulation is build through the identification of agents with the behavior of agent.  The relationship is identified through the agent interaction with the environment.  The agent related data is getting requisite and then validation process of agent behavior is done.   In last, run the model and analyze of output for the effective implementation of agent based modeling in the organization. (North & Macal, 2006)

Agent: The identification of agents and their roles and responsibilities are towards managing the operations of business. The attributes of agent is defined with their core duties and have spate paradigm of supplier and manufacturer.

Environment: The supply chain environment is allocated for the interaction of flow of movement materials and information.

Agent method: Agent to agent or either environment with agent interactions is identified.

Agent interaction: The process interaction is derived in which the interaction is done in the simulation.

Implementation: By using computational software, implement agent model.

Use in simulation:

The detailed alternative solutions of the problem are recognized through the simulation process. This also ensures the risk management for the alternative conditions that how the company has to become resilient with the risk occur. The model of simulation is used in the supply chain is as an aid intuition. Simulation is used in the concept of management field that is related to the social sciences.  The improvement in the existing model of supply chain would be enhanced through the simulation.  The evaluation of supply chain reengineering efforts has great impact on business operations and gain operational excellence in the supply chain. (Um, Lu, & Hall, 2010)

The multi agent based simulation is the integration of advancement of technology that gives the solution of doing science.  The capabilities of growing structure of computer capabilities and focuses on the artificial intelligence is gained through the agent based modeling of simulation in the supply chain.

The agent based modeling of simulation is also useful in the strategic decision-making.  The modeling structure is the major focus in the business to consumer market.  The agents used the models by the product providers, several behaviors and consumer’s behaviors through simulation. The best identification of product characteristics, satisfaction and cheapest offerings are the specifications of simulation for the consumer. The conventional communication system is established through the multi agent based system investigation.

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Example:

Net logo is the example of agent based modeling used for the programming language between the agents. It is also called integrated modeling environment. The net logo is the programming language that understands the agents in the form of observer, turtles, links and patches. The net log is the powerful platform of scientific modeling that retains the design of the system in well effective manner.

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 The net log is the conceptual design, excellent documentation, and ease of use in collaborating with the agents. In the case of the supply chain, the software is installed in both the ends to execute the business operations in well manner. The multi-agent programmable modeling environment is executed in business planning and used by agents to early replenishment of inventory management. This shows that this software is implemented in the supply chain system that gives desired outcomes of operational excellence.

References:

Helbing, D., & Balietti, S. (2012). “How to Do Agent-Based Simulations in the Future: From Modeling Social Mechanisms to Emergent Phenomena and Interactive Systems Design. Springer-Verlag Berlin Heidelberg.

Hernández, J. E., Alemany, M., Lario, F. C., & Poler, R. (2009). SCAMM-CPA: A supply chain agent-based modelling methodology that supports a collaborative planning process. Retrieved July 2, 2015, from http://www.scielo.org.co/pdf/inno/v19n34/v19n34a08.pdf

Mele, F. D., Guillén-Gosálbez, G., Espuna, A., & Puigjaner, L. (2007). Agent-based systems for supply chain management. Retrieved July 2, 2015, from http://egon.cheme.cmu.edu/ewocp/docs/GonzaloEWO-GG-11Dec.pdf

North, M. J., & Macal, C. M. (2006). TUTORIAL ON AGENT-BASED MODELING AND SIMULATION PART 2: HOW TO MODEL WITH AGENTS. Winter Simulation Conference.

Um, W., Lu, H., & Hall, T. J. (2010). A Study of Multi-Agent Based Supply Chain Modeling and Management. Scientific Research.

Zhu, X. (. (2008). AGENT BASED MODELING FOR SUPPLY CHAIN MANAGEMENT: EXAMINING THE IMPACT OF INFORMATION SHARING. Retrieved July 2, 2015, from https://etd.ohiolink.edu/!etd.send_file?accession=kent1226538465&disposition=inline

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