Multiagent based Open Source for Supply Chain ...

International Conference on Information Communication & Embedded Systems (ICICES 2014)

Multiagent based Open Source for Supply Chain management using JADE Mr.Rolls John

Prof.S.Balakrishnan

PG Scholar Rajiv Gandhi College of Engg Sriperumbudur [email protected]

Associate Professor, Dept of CSE Rajiv Gandhi College of Engg Sriperumbudur [email protected]

Abstract— Supply chain management (SCM) is a very challenging problem that us leveraging the e-commerce explosion. Today’s supply chains are essentially static, because they rely on long-term relationship among key trading partners. Dynamic practices are vital because they offer better matches between suppliers and customers as market conditions change. Multi-agent systems (MAS) offer new perspectives compared to conventional, centrally organized architectures in the scope of supply chain management (SCM). Their structure inherently meets the requirements of decentralized supply chains, whereas conventional SCM systems are often restricted in terms of dynamic behavior, handling severe disturbances at supplier sites as well as dealing with highly customized or complex products. Since necessary data are not available within the whole supply chain, an integrated approach to production planning and control taking into account all the partners involved is not feasible. In this paper a MAS architecture integrating various intelligent agent systems is presented to address the problem. Keywords— Supply Chain Management, Agent Technology, Multi-Agent System, JADE

I.

Introduction

Today’s business environment industry is competitive and they are able in recognizing the importance of an efficient SCM. Supply chain can be viewed as a network of facilities and distribution options which performs all the functions like procurement of materials, transformation of these materials into intermediate and finished products and the dispersion of these finished products to customers. This is known as the autonomous or the semi autonomous business entities which performs all the process associated with the flow and transformation of goods and materials are serviced from the raw material stage through the end user. The objective of the supply chain management is to create and to distribute merchandise at right quantities, to the right locations, at the right time to minimize system wide costs at the same time it will meet the requirements at the service level. To clear the objective, an effective support should be extracted from modern information technology and information system. In this case, many such effective information systems have been

developed to assist the SCM from the basic enterprise based resource planning into many newly developed advanced planning and scheduling system and e-commerce solutions. The capability of these currently working information systems is to support collaborative planning and the control is limited in the supply chain system wide level on the basis of complexity and dynamics of the supply chain in a globalized business environment. For conceptualization, agent based system technology has been applied as a new paradigm for designing and implementing the software package which gives the potential to overcome the limitations of the information systems for the SCM. To optimize a supply chain execution, the operations of its parts must be in an organized manner. But the dynamics of these enterprises and the market face certain difficulties such as, the materials are delayed because of shipment, the production facilities experience downtime, workers fall sick, customer change order or cancel it and there are other issues also which cause deviations from the actual plan. Therefore the demand of the real time coordination of the supply chain is critical in the global marketplace due to fast changing trends and shortening in product life cycles. The information sharing and information technology makes the coordination possible. Internet paves the major contribution as the information technology is to enable many companies to directly have contact with the clients without the distance intervention or time zone. One company in one directional way cannot govern the collaborations in supply chains, coordination of companies through autonomous participation is needed. Here, agent technology is regarded as one of the best candidates for supply chain management for the above reasons [4]. The raw materials are acquired, transformed, and delivered to customers [7], [13] through a worldwide network of suppliers, warehouses, factories, distribution centers and retailers known as the supply chain. This supply chain includes the activities such as flow and transformation of goods from the raw material stage to the end user it also includes the information flows associated with it [8], [20], [23]. The novel features of the agent include the ability to distribute orders preferentially among the clients, to choose

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International Conference on Information Communication & Embedded Systems (ICICES 2014) the competing vendors, to manage production and inventory, to determine the competitive behavior and price. To sustain the global competitiveness and responsiveness to the changes in the market, every manufacturing enterprise has to be integrated with the suppliers, partners and customers and not only with the management systems such as purchasing, production, design, scheduling, planning, control, resources, transport, materials, personnel, quality etc. The integration is made through heterogeneous software and hardware environments. The activity of the supply chain comprises how to design, deliver, build and use a product or service. The supply chains extend to multiple enterprises which includes providers, manufacturers, warehouses, transportation carriers, retailers, customers and details used in forecasting, ordering and inventory and the production details to coordinate the decisions made by the management for the betterment at multiple stages throughout the extended enterprise [1]. The main goal of the Supply Chain Management is to plan and coordinate all the activities in a supply chain. These activities consist of many participants and the key aspect for efficient trading is coordination. II.

RELATED WORK AND DIRECTIONS

In supply chain management, improving the efficiency of the overall supply chain is of central interest. Because of market globalization and the advancement of e-commerce the importance of supply chain network is increasing. It is very difficult for different companies in supply chains to share information. A supply chain can produce products for multiple markets. Likewise, an individual company is likely to receive only limited visibility of the supply chain structure, which makes it difficult to make future demand estimations, because the shape of demand propagation through the supply chain depends on the capabilities and strategies of companies along the path from the markets to the company [4]. S. Yung. [13] states that research in coordination of supply chains can be categorized into the following four regions: 1. Modeling of Supply Chains – the processes and functionality of supply chains must be devised and coordinated efficiently to attain better performance. Recently, constraint network model has been studied and applied. 2. Modeling of Information Flows – which provides the communication among facilities within the supply chains, where real-time data are critical in supporting decision making. It enables quick response and accurate data transmission. Electronic data interchange (EDI) is one of the most popular applications. However, EDI is a closed environment for installations within the supply chain. The internet offers a channel to support communication for both the facilities within and outside the supply chains. 3. Human Computer Interface (HCI) – the amount of data generated from a supply chain is overwhelming. It is

important to have a good interface for users to input and retrieve data or information. Recently, much research has focussed on software agents to model the behavior of the users and use the captured behavior to support design of better graphical user interface (GUI). 4. Optimization Method – optimization is an important research area to search for better resource allocation in supply chain management. Some mathematical models have been applied to increase the performance of supply chains. But such research can be computationally intensive if the number of facilities is large. S. Srinivasan. [1] proposed a multi-agent architecture for integrated dynamic scheduling of the steel pipe industry, each agent performs a specific function of the organization and share the information with other agents. X. Xu and J.Lin [5] proposed an advancing mechanism that integrates High Level Architecture with multi-agent distributed simulation to meet the time management in supply chain simulation. G. Seitz. [6] Proposed an agent-based architecture for appending sensor data to a digital product memory in a generic manner. V. Misra. [8] Survey the Supply Chain Management Systems and states that, six characteristics define current supply chain management philosophy: 1) Shared Information, 2) Organizational Relationships, 3) Inventory Management, 4) Total Pipline Coordination, 5) Readiness to adopt Flexibility and 6) Costing Issues. They regarded Agent-Based SCM is the vision and states that: Agents can help transform closed trading partner networks into open markets and extend such applications as production, distribution, and inventory management functions across entire supply chains spanning diverse organizations. R. Carvalho and L. Custodio [9] proposes a Multi-agent system for Managing Supply-Chain Problems. They utilized their systems in chemistry industry and the Hewlett-Packard. M. Paolucci. [12] proposes a multi-agent based system that would enable small and medium-size manufacturing organizations to dynamically achieve cost-effective aggregate sales and operations plans in supply chain contexts. M. Uppin and S. Hebbal [19] outlines two major outcomes of the literature survey is that information sharing is the most important requirement of efficient supply chain and multi agent modeling is most suitable for designing of supply chains. V. Kumar and S. Srinivasan [20] review SCM system with short explanation and conclusion to this system. M. Abdoli and B. Al-Salim [21] provide a conceptual framework for implementing a sales agent at Internet-based stores (e-stores). As the effectiveness of centralized command and control in SCM starts to be questioned, there is a critical need to organize supply chain systems in a decentralized and outsourced manner. Agent-based models can easily be spread across a network due to their modular nature. Therefore, the

ISBN No.978-1-4799-3834-6/14/$31.00©2014 IEEE

International Conference on Information Communication & Embedded Systems (ICICES 2014) distribution of decision-making and implementation capabilities to achieve system decentralization is possible through models of operation with communication among them. The ontology structure of JADE framework is, in our opinion, one of the best designed to address the issues of accessing and sharing information pertinent to a specific application. In this paper, the proposed model consists of seven factors that are working in concert to maintain supplying, manufacturing, inventory and distributing the cables which specified in details in the proposed model section. The main operations of the software agents include: managing all other agents, receiving orders, check the inventory, issue the order of raw materials from suppliers, production, financing, storing the information of stock, components and material. In addition to communication protocols among agents. Information sharing among neighboring agents that is very important to the SCM for decision making are verified and when we make negotiation we consider not only price but also review point and delivery time. The instructions for building Supply chain management systems are outlined as follows: 

Fuzzy set theory approach helps to convert decision makers’ experience to meaningful results by applying linguistic values to evaluate each criterion and alternative providers. Fuzzy Principal Component Analysis can be used in “Automation in Construction”.

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An agent architecture that combines the use of Component-based Software Engineering and Aspect- Oriented Software Development.

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Agent – based modeling and simulation is a new approach to modeling systems comprised of interacting autonomous agents.

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Simulation of any number of agents plus heuristics for decision making. Agents can be used to rule-based system. Heuristic search or problem decomposition methods, random search methods, such as genetic algorithms, and negotiation methods may not guarantee global optimality, but their solutions are quicker to get and the differences from the optimal ones may be acceptable.

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Operations Research techniques and artificial intelligence techniques are used to modify plans while minimizing impacts on performance.

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A case based reasoning system is an excellent option especially in an SCM environment where decisions have to be taken instantaneously.

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Mobile – agents can be used to enhance the technology of building SCMs.

III.

SUPPLY CHAIN MANAGEMENT

Supply Chain Management is defined as “the integration of key business processes from end user through original suppliers that provide products, services, and information that add value for customers and other stakeholders [8], [14]. It is an important management paradigm to interpret and analyze the flow of goods, services and the accompanying values reaching to the consumers followed by the processes of purchasing, production and distribution by combining and connecting the whole system [4], [15]. SCM involves managing the flow of material and information through multiple stages of manufacturing, transportation and distribution with the overall process. The objective of maintaining low inventories without compromising customer service level. The effective practice of SCM is critical to participating companies especially in today’s business trend whereby companies are geographically distributed throughout the globe [5]. Supply Chain Management is the most effective approach to optimize working capital levels, streamline accounts receivable operations, and eliminate excess costs linked to payments. Analysts estimate that such efforts can improve working capital levels by 25%. Today, the best companies in a broad range of industries are implementing financial supply chain management solutions to improve job performance and free cash resources for growth and innovation [3]. In addition Supply Chain Management is about managing the physical flow of merchandise and related flows of information about purchasing through production, distribution and the delivery of the finished product to the customer. This involves thinking beyond the established boundaries, strengthening the linkages between the supply chain functions and finding ways to pull them together. The result is a system that offers a better service at a lower price. Many managers now understand that actions taken by one member of the chain can influence the profitability of all others in the chain. Two houses are increasingly thinking in terms of competing as part of a supply chain against other supply chains, rather than as a single firm against other private firms. Also, as firms successfully streamline their own operations, the next opportunity for improvement is through better coordination with their suppliers and customers. The costs of poor coordination can be extremely high. To the best of our knowledge an integrated, agent based methodology analysis and design approach to the supply chain procurement, production and customer order bidding problem has not been addressed in the literature thus far. Thus giving the notion of Multi-Agent Systems are necessary in these fields [2]. IV.

FIPA-OS

FIPA-OS (FIPA Open Source) is an open agent platform originating from Nortel Networks. The platform supports communication between multiple agents using an agent communication language which conforms to the FIPA (Foundation for Intelligent Physical Agents) agent standards. A key focus of the platform is that it supports openness. This

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International Conference on Information Communication & Embedded Systems (ICICES 2014) is naturally supported by the agent paradigm itself and by the design of the platform itself, whose parts have loose coupling such that extensions and innovations to support agent communication can occur in several key areas. The openness is further emphasized in that the platform software is distributed and managed under an open-source licensing scheme. FIPA-OS is being deployed in several domains including virtual private network provisioning, distributed meeting scheduling and a virtual home environment. It has been demonstrated to interoperate with other heterogeneous FIPA compliant platforms and is in use in numerous institutions around the world. A. FIPA and other agent standards In the context of FIPA, an agent1 is an encapsulated software entity with its own state, behavior, thread of control, and an ability to interact and communicate with other entities – including people, other agents, and legacy systems. This definition puts an agent in the same family as objects, functions, processes, and daemons but it is also distinct in that it is at a much higher level of abstraction. The agent interaction paradigm differs from the traditional client-server approach: agents can interact on a peer-to-peer level, mediating, collaborating, and co-operating to achieve their goals. A common (but by no means necessary) attribute of an agent is an ability to migrate seamlessly from one platform to another whilst retaining state information, a mobile agent. One use of mobility is in the deployment and upgrade of an agent. Another common type of agent is the intelligent agent, one that exhibits 'smart' behavior. Such 'smarts' can range from the primitive behavior achieved through following user-defined scripts, to the adaptive behavior of neural networks or other heuristic techniques. In general, intelligent agents are not mobile since, in general, the larger an agent is the less desirable it is to move it; coding artificial intelligence into an agent will undoubtedly make it bigger. There is an exception to this last statement, 'Swarm' intelligence. This is a form of distributed artificial intelligence modeled on ant-like collective intelligence. The ant-like 'agents' collaborate to perform complex tasks, which individually they are unable to solve due to their limited intelligence (e.g. ant-based routing) (Schoonderwoerd, 1996). Another prevalent, but optional, attribute of an agent is anthropomorphism or the 'human factor': this can take the form of physical appearance, or human attributes such as goaldirected behavior, trust, beliefs, desires and even emotions. There are three important agent standardization efforts which are attempting to support interoperability between agents on different types of agent platform: KQML community, OMG’s MASIF and FIPA. Of these three: KQML and FIPA both define interaction in terms of an Agent Communication Language (ACL) whereas MASIF defines interaction in terms of Remote Procedure Calls (RPC) or Remote Method Invocation (RMI). In contrast to the traditional RPC-based paradigm, the ACL as defined by FIPA provides an attempt at a universal message-oriented

communication language. The FIPA ACL describes a standard way to package messages, in such a way that it is clear to other compliant agents what the purpose of the communication is. Although there are several hundred verbs in English, which correspond to performatives, the ACL defines what is considered to be the minimal set for agent communication (FIPA ACL consists of 20 or so performatives). This method provides for a flexible approach for communication between software entities exhibiting benefits including: • Dynamic introduction and removal of services • Customized services can be introduced without a requirement to re-compile the code of the clients at runtime • More de-centralized peer-peer realization of software •

A universal message based language approach providing consistent speech-act based interface throughout software

• Asynchronous entities

message-based interaction

V.

between

JADE

JADE is a middleware developed by TILAB. It is a software framework fully implemented in Java language to simplify the development of applications. Using a middleware it simplifies the implementation of MAS, the middleware complies with the FIPA (Foundation for Intelligent Physical Agents) specifications and a set of graphical tools which support the debugging and deployment phases. Such a system

Agent Based application

Container

Container

Container

can be implemented with the help of JADE. Fig. 1. JADE ARCHITECTURE

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International Conference on Information Communication & Embedded Systems (ICICES 2014) VI.

Fig. 2. SCM Multi-agent architecture

SCM Multi agent architecture

A typical supply chain may involve a variety of participants, such as (i) customers (ii) retailers (iii) wholesalers/ Distributors (iv) Manufacturers and (v) raw material supplier. The objective of every supply chain is to maximize the overall value generated, which is normally measured through profitability. Chopra et.al advocate that all processes in a supply chain can be broken down into the following four cycles: 

finished items and (iii) direct sales of finished items to customers. The customer agent typically represent real customers and firms that are willing to buy finished items. This agent must implement a strategy for selecting finished goods based on its preferences. This decision affects all sup-problems, but has a stronger influence in the direct sales sub-problem.

Customer order cycle - processes directly involved in receiving and filling customer’s orders;

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Replenishment cycle - processes involved in replenishing retailer inventory with a distributor;

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Manufacturing cycle – processes involved in replenishing distributor inventory;

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Procurement cycle – processes necessary to ensure that materials/ components are available for manufacturing according to the schedule.

In a direct sales model, such as the one used by Dell Inc. the manufacturers fill customer orders directly. Retailers, wholesalers and Distributors are bypassed in this type of supply chain, which ends up with only three participants – Customers, Manufacturers and Suppliers. This is probably the most dynamic practice used by the market nowadays, and this is the main reason why we decided to implement our multiagent system based on this SCM model. The architecture proposed uses a multi-agent approach in order to build a flexible and general design for a dynamic supply chain. Each agent can be implemented with a different AI technique, which permits a system designer to test many diverse strategies and decide the optimal combination of these techniques. The agents also use a central knowledge base as a key component for collaboration. Agent store results and information in the knowledge base so that other agents can use it to solve their problems. The following figure3 represents architecture of multi-agent system.

VII.

CONCLUSION AND FUTURE SCOPE

Supply Chain encompasses all those activities needed to design, manufacture and deliver a product or service needs a mechanism or frame work for information sharing. Agentbased manufacturing is a new way of thinking about and applying information. With this idea an attempt is made to provide a multi agent system model for the supply Chain management. The proposed FIPA-OS based supply chain architecture is easily adaptable since changes occurred in the configuration of the supply chain, or in the production within the supply chain, can be managed by adding new entities into the system or enhancing the existing ones. The potential of agent technologies and the use of FIPA ACL as a communication approach based on commitment can be exploited to build layers of intelligent interaction and knowledge-sharing. Such mechanisms open enormous potential towards the design of self-organizing, reconfigurable architectures needed in a dynamic environment such as web-Centric global supply chain management. In the proposed model each agent performs a specific function of the organization and share the information with other agents. There by the most important requirement of effective supply chain i.e. information sharing is achieved in the proposed model. At the same time this agent based approach provides reliable and agile systems, which will enable manufacturing organizations of the future to accommodate ever changing needs of its customers.

The main focus of the proposed design is to tackle separately important sub problems of a supply chain: (i) procurement of components (ii) production and delivery of

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