Study on Knowledge Spillover in Supply Chain-Style Industrial Cluster Based on Multi-Agent

2011 ◽  
Vol 58-60 ◽  
pp. 2417-2422
Author(s):  
Bin Qing Cai ◽  
Guo Hong Chen ◽  
Yi Jun Dai ◽  
Xin Huan Huang
Keyword(s):  
Supply Chain ◽  
Social Network ◽  
Supply Chains ◽  
Industrial Cluster ◽  
Knowledge Spillover ◽  
Knowledge Flow ◽  
Flow Mechanism ◽  
Simulation Based ◽  
Multi Agent

According to social network relations strength, enterprises in industrial cluster supply chains are classified and the structure of supply chain style-industrial cluster is description. The enterprises selected mechanism and the knowledge flow mechanism in industrial cluster supply chain is designed, and then the simulation based on multi-agent are carried out. According to the simulation, the process of process of knowledge spillover in industrial cluster supply chain is draw and various enterprises influence on knowledge spillover in industrial cluster is analyzed.

The Use of Multi-Agent Systems in Managing Sustainable Supply Chain

2013 ◽  
Vol 315 ◽  
pp. 108-112
Author(s):  
Majid Aarabi ◽  
Muhamad Zameri Mat Saman ◽  
Kuan Yew Wong
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supply Chains ◽  
Sustainable Supply Chain ◽  
Multi Agent Systems ◽  
Chain Management ◽  
Agent Based ◽  
Goods And Services ◽  
Proposed Model ◽  
Multi Agent

The main purposes and challenges in supply chain management are reducing cost and time. Significantly, factors such as the competition of markets in the globe, limitation of energy, raw and virgin materials, environmental protection crisis and increasing of global population dramatically are causing unprecedented issues for the worldwide supply chains for providing goods and services to customers efficiently and effectively. The sustainability approach for Supply Chain Management (SCM) considers the 6Rs principles in four main stages of the supply chains: Pre-manufacture, Manufacture, Use and Post-use. The use of Multi-Agent System (MAS) prepares the most important requirements of an effective sustainable supply chain. At the same time, this agent-based approach provides reliable and agile systems, which will enable enterprises to accommodate ever changing needs of their customers in the future. In this article, the use of MAS for optimal Sustainable Supply Chain Management (SSCM) is reviewed and the integrated functioning of certain agents resulting in information sharing is also demonstrated. With this idea, an attempt is made to provide a MAS model for the SSCM. In the proposed model, each agent performs a specific function of the organization and shares information with other agents. In order to describe this multi-agent based approach, a simple case study is given to illustrate the sustainable supply chain operations.

scholarly journals A multi-agent based system with big data processing for enhanced supply chain agility

2016 ◽  
Vol 29 (5) ◽  
pp. 706-727 ◽  
Author(s):  
Mihalis Giannakis ◽  
Michalis Louis
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Semantic Web ◽  
Supply Chains ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Agent Systems ◽  
Supply Chain Agility ◽  
Multi Agent

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

scholarly journals Mediating Dynamic Supply Chain Formation by Collaborative Single Machine Earliness/Tardiness Agents in Supply Mesh

2014 ◽  
Vol 2014 ◽  
pp. 1-21
Author(s):  
Hang Yang ◽  
Simon Fong ◽  
Yan Zhuang
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Single Machine ◽  
Intelligent Agents ◽  
Textile Industry ◽  
Make To Order ◽  
Simulation Based ◽  
Trading Partners ◽  
The Right ◽  
Complex Scenario

Nowadays, a trend of forming dynamic supply chains with different trading partners over different e-marketplaces has emerged. These supply chains, which are called “supply mesh,” generally refer to heterogeneous electronic marketplaces in which dynamic supply chains, as per project (often make-to-order), are formed across different parties. Conceptually, in a supply mesh a dynamic supply chain is formed vertically, mediating several companies for a project. Companies that are on the same level horizontally are either competitors or cohorts. A complex scenario such as this makes it challenging to find the right group of members for a dynamic supply chain. Earlier on, a multiagent model called the collaborative single machine earliness/tardiness (CSET) model was proposed for the optimal formation of make-to-order supply chains. This paper contributes the particular agent designs, for enabling the mediation of CSET in a supply mesh, and the possibilities are discussed. It is demonstrated via a computer simulation, based on samples from the U.S. textile industry, that by using intelligent agents under the CSET model it is possible to automatically find an ideal group of trading partners from a supply mesh.

Cross-docking Centre Location in a Supply Chain Network: A Social Network Analysis Approach

2018 ◽  
Vol 19 (3_suppl) ◽  
pp. S218-S234 ◽  
Author(s):  
Prashant Barsing ◽  
Yash Daultani ◽  
Omkarprasad S. Vaidya ◽  
Sushil Kumar
Keyword(s):  
Supply Chain ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Supply Chains ◽  
Food Supply ◽  
Humanitarian Relief ◽  
Cross Docking ◽  
Relief Operations ◽  
The Relationship

The level of uncertainty, unpredictability and complexity is magnified in a food supply chain as compared to the conventional supply chains such as automobile and FMCG. This is mainly because of the short product shelf life and the need of high variety. This necessitates the food industry to adopt various quick response systems to achieve effective supply chain management. The situation becomes even more critical when dealing with humanitarian relief operations where time window is very short (usually 24 hours). One of the solutions which are adopted in modern food supply chains is to locate cross-docking centre (CDC). Cross-docking is used to reduce the turnaround time of the food products. The practical situation is complex as it caters to multiple customers. The number of suppliers, in such cases, plays a significant role. Selection of a right CDC is, therefore, a crucial task. It is a strategic decision and needs to be taken by considering the relationships between each stakeholder present in the supply chain. In this article, we present an approach to select one (or few) CDC/s facilities among n CDCs. The method is based on the relationship between each actor (actors are the stakeholders in the supply chain). The relationship is in terms of the physical flow of materials or information flow or another kind of flows or relationships that connects them to form a network. These network characteristics are required to find out key stakeholders. The present article proposes the application of social network analysis (SNA) to analyse the characteristics of the network, thus helping supply chain managers to locate strategic CDCs considering both qualitative and quantitative aspects. The proposed methodology can be easily extended to locate temporary warehouse site in the context of humanitarian relief operations.

A new transshipment policy in cluster supply chains based on system dynamics

2018 ◽  
Vol 52 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Bo Yan ◽  
Lifeng Liu
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Supply Chains ◽  
Industrial Cluster ◽  
Inventory Level ◽  
Network System ◽  
Supply Chain Network ◽  
Proposed Model ◽  
Total Inventory ◽  
The Cross

In this paper, the cross-chain inventory emergency supplementary of two single supply chains is investigated to simulate the transshipment of the supply chain network system in the industrial cluster supply chains. We assume that each single supply chain is composed by a manufacturer, a wholesaler and a retailer. Besides, a new transshipment policy based on system dynamics (SD) is proposed in this paper, called the model of the cross-chain inventory transshipment between two enterprises from both the same tier and different tiers. The new proposed model is different from the model of the cross-chain inventory transshipment between two enterprises at the same tier and the model of the cross-chain inventory transshipment between two enterprises at different tiers, which have been researched by previous scholars. Some comparisons are made among the three models. It is proved that the new proposed model can improve the customer satisfaction level (CSL) and lower the total inventory level than the two other models existing currently.

A-TEAM BASED SUPPLY CHAIN MANAGEMENT AGENT ARCHITECTURE

2009 ◽  
Vol 18 (06) ◽  
pp. 801-823 ◽  
Author(s):  
YUJUN ZHENG ◽  
JINQUAN WANG ◽  
JINYUN XUE
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Problem Solving ◽  
Supply Chains ◽  
Agent Architecture ◽  
Chain Management ◽  
Agent Based ◽  
Multi Agent ◽  
Communication And Coordination

Today's supply chains increasingly involve complex sets of processes, objectives and constraints, and therefore agent-based architectures for supply chain management (SCM) become much more difficult to implement and maintain. The paper presents a multi-agent architecture for specifying, analyzing and developing SCM systems, in which asynchronous teams (A-Team) of problem solving agents exchange results within populations that provide effective management of information flows in supply chains, and cooperate to produce sets of non-dominated solutions that show the tradeoffs between objectives. Our approach distinguishes itself by improving problem-solving efficiency based on a diverse set of algorithms without complicated synthesis efforts, removing the focus from agent communication and coordination details, and improving reusability, flexibility and extensibility by supporting object-oriented and component-based programming style. We examine the effectiveness of the architecture through a real-world case study and experimental results.

Simulation of Stock Strategies in Dynamic Supply Chains

2012 ◽  
Vol 472-475 ◽  
pp. 3251-3257
Author(s):  
Jing Li ◽  
Wei Liu
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Two Stage ◽  
Safety Stock ◽  
Agent Model ◽  
Maximum Profit ◽  
Financial Benefits ◽  
Significant Difference ◽  
Auction Mechanisms ◽  
Multi Agent

This paper is focused on the study of (T, S) stock strategies in dynamic supply chains. The dynamic supply chain means the retailer can change his suppliers in every purchase period for more profits. Four categories of two-stage supply chain structures consisting of multiple suppliers and a single retailer are considered. Two categories of auction mechanisms, single-winner or multi-winner auction, are used in this paper. A multi-agent model is developed to study these four categories of supply chains. The results of experiments show that, with the decrease of safety stock, the tendencies of the retailer’s profit are changed under different structures. Also, the optimal (near-optimal) safety stock, corresponding to the maximum profit, shows significant difference under different structures. The results of this paper demonstrate that the safety stock can be significantly changed and financial benefits can be achieved while working under different supply chain structures with (T, S) strategy.

scholarly journals Adapting transport modes to supply chains classified by the uncertainty supply chain model: A case study at Manaus Industrial Pole

2017 ◽  
Vol 5 (1) ◽  
pp. 39 ◽  
Author(s):  
Fabiana Lucena Oliveira ◽  
Aristides da Rocha Oliveira Junior ◽  
Luiza M. Bessa Rebelo
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Air Transport ◽  
Primary Data ◽  
Chain Model ◽  
Theoretical Argument ◽  
Supply Chain Model ◽  
Transport Modes

<p class="FonteResumo">This paper discusses transport modes supporting Uncertainty Supply Chain Model (USCM) in the case of Manaus Industrial Pole (PIM), an industrial cluster in the Brazilian Amazon that hosts six hundred factories with diverse logistics and supply chain managerial strategies. USCM (Lee, 2002; Fisher, 1997)develops a dot matrix classification of the supply chains considering several attributes (e.g., agility, cost, security, responsiveness) and argues that emergent economies industrial clusters, in the effort to keep attractiveness for technological frontier firms, need to adapt supply chain strategies according to USCM attributes. The paper takes a further step, discussing which transport modes are suitable to each supply chain classified at the USCM in PIM´s case. The research´s methods covered the use of PIM´s statistical official database (secondary data), interviews with the main logistical services providers of PIM and phone survey with a sample of firms (primary data). Findings confirm the theoretical argument that different supply chains will demand different transport modes running at the same time in the same industrial cluster (Oliveira, 2009). In the case of PIM, this implies investments on port and airport infrastructure and a strategic focus on air transport mode, due to (1) short life cycle of products, (2) distance from suppliers, (3) quick response to demand and (4) the fact that even PIM´s standard products use, in average, forty per cent of air transport at inbound logistics.</p>

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