A MULTI AGENT DECISION TREE ALGORITHM FOR SUPPLY CHAIN MANAGEMENT

The issue of interest here is the behaviour of decision agents in supply chain management. The study uses a managerial framework to organize supply-related tasks to the behaviour of specification stantiations of decision agents. The reasons why organizations might elect to invest supply chain management responsibilities in decision agents rather than human functionaries are illustrated. Finally, this research presents a final construct for optimal agent-based decision making opportunities. The implication is that a shift of power from humans to computers is shown to bequite effective on technically tractable decision situations


INTRODUCTION
From the viewpoint of management science, managers must rationally allocate the limited resources at the managers' disposal by making optimal decisions that result in the ultimate outcome of profit maximization. Thus, the content of managerial rationality requirements is to make decisions that maximize an organization's benefits. Supply chain management (SCM) is a proven strategic business structure that's goal is to implement organizational decision making that results in optimal performance. It has gained wide acceptance in recent years because it helps managers make optimal decisions that rationally allocate resources that increasing are supplied by a global network of suppliers. In addition, customer demands for variety, quality, delivery, and speed require the supply chain to operate "slicker" as its performance and cost is pivotal to overall profit maximization. While ideal rational decision making in SCMis an impossibility when viewed as comprehensive rationality, SCM is a collection of decisions made under the constraints of bounded rationality that can approximate optimal decisions. Supply chain management systems are instantiations of management support systems which provide instances of decision technology. They are composed of a set of intelligent decision agents, which interact with other decision agents to plan and execute one or more responsibilities. Decision agents are an "autonomous, goaloriented software process that operates asynchronously, communicating and coordinating with other agents as needed" (Fox et al., 2000).
This paper is organized as follows. First, this research discusses SCM and organizational decision making. It then defines the three levels of organizational decision making and the computer-based constructs that can be used in the optimization of supply chain performance. These levels have been identified in the management literature as strategic level (unstructured), tactical (semistructured),and operational level(structured) decision making (Gorry andMorton, 1971). DDDs and decision agentscan be employed in the tactical andoperational levels of decision making.Specific instantiations of decision agents andDDDs and their references in the literaturewill be outlined and a concluding construct is represented.

LITERATURE SURVEY
Supply chain management (SCM) is a provenbusiness strategy that's goal is to implementdecision making that results in optimalperformance. Supply chains can exist in bothmanufacturing and service organizations,and they are principally concerned with theflow of products and information betweenthe organizations in the supply chainnetwork, the procurement of materials,transformation of materials into finishedproducts, and distribution of those productsto the end customers. Today's informationdriven,integrated supply chains are enablingorganizations to reduce inventory and costs,add product value, extend resources,accelerate time to market, and retaincustomers. In the last few years,organizations that are supply chaininnovators have migrated from buildingexcellence in its supply chain to making useof the supply chain to create added-value.

PROPOSED WORK
During the supply chain organization process, each agent can receive an invitation tojoin the chain as supplier and, based on its actual resources, productive capabilitiesand economical convenience, it can decide if joining the chain or no. To collaboratein the chain, the agent can ask other agents for products/services it needs for its ownbusiness process. In this case, it acts as customer and invites other agents to join the chain for satisfying a certain order. In practice, before joining the supply chain, the agent needs to organize a sub-chain for its own business process. Once an agent knows it can join the supply chain, it replies to the invitation informing about its availability and the conditions it wants to impose for being part of the collaboration (for example price and temporal conditions). Therefore, a supply chain is the result of a set of negotiations among the agents belonging to the same group. To consensus, two different kinds of information flow across the agent network. in figure 2, the up-down information flow represents the invitations sent to agents for being part of the supply chain, while the bottom-up information flow represents the information flowing from suppliers to customer about their conditions to join the supply chain. During the negotiations, all the agents are in competition one each other; their behavior can be oriented to maximizing their business volume constrained by the quality of the final product, their productivity capability and the minimum profit they want to get. The supply chain can be built choosing all the agents that, with the highest probability, could assure the success of the final supply chain and would collaborate to satisfy the final customer's order. In the following, we assume that the entire supply chain can be modeled as a tree; at each level, a sub-tree represents a subchain. In our formulation, at each node of the tree an agent provides a particular goods or service needed at higher levels to provide the product required by the customer. However, the production of this goods/services can require the cooperation of other agents. Therefore it can be necessary to establish a set of collaborations with other agents, i.e. a new sub-chain. The organization of the entire supply chain reduces to recursively organize each sub-chain as showed in figure1 . The problem of organizing a supply chain is therefore addressed by dividing it into sub-problems of lower complexity. The entire supply chain can be organized considering sub-optimal solutions at each node of the tree. Whilst in general the solution will not be globally optimal, under the assumption of independence of the sub-tree, the final solution will be optimal. This assumption does not limit the applicability of our system because it is reasonable to assume that at each node of the supply chain independent business processes would be developed.

EXPERIMENAL RESULTS
To evaluate the performance of the proposed work for SCM, the textile dataset collected from open source. The dataset contains labels, Supplier id, quantity, cost, item id, material, size, quantity, Product Cost and dealer cost values. These are given for the proposed improved C4.5 algorithm. The obtained results and its performance are measured and compared with existing technique for the input textile dataset.   Figure 1 shows an example of decision network used by each customer agent toorganize its own sub-chain.