Multi-agent Based Integration of Production and Distribution Planning Using Genetic Algorithm in the Supply Chain Management

Author(s):  
Byung Joo Park ◽  
Hyung Rim Choi ◽  
Moo Hong Kang
2008 ◽  
pp. 2598-2617
Author(s):  
Jianxin Jiao ◽  
Xiao You ◽  
Arun Kumar

This chapter applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semi-autonomous problem-solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturingsupply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.


Author(s):  
Jianxin Jiao ◽  
Xiao You ◽  
Arun Kumar

This chapter applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semi-autonomous problem-solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturingsupply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.


2012 ◽  
Vol 1 (1) ◽  
pp. 38-54
Author(s):  
Babak Sohrabi ◽  
MohammadReza Sadeghi Moghadam

The present study, using genetic algorithm, tries to improve material flow management in supply chain. Consequently, in this paper, an integrated supply-production and distribution planning (SPDP) is considered despite the fact that in most of the Iranian industrial firms, SPDP is done independently. The effective use of integrated SPDP not only enhances the performance rather decreases inventory cost, holding cost, shortage cost and overall supply chain costs. A quantitative mathematical model is used to the problem articulation, and then it is solved by applying heuristic genetic algorithm (GA) method. The proposed model with genetic algorithm could provide the best satisfactory result with the minimum cost. The reliability test was carried by comparing the model results with that of the amount of variables.


2013 ◽  
Vol 315 ◽  
pp. 108-112
Author(s):  
Majid Aarabi ◽  
Muhamad Zameri Mat Saman ◽  
Kuan Yew Wong

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.


2012 ◽  
pp. 1316-1333
Author(s):  
Babak Sohrabi ◽  
MohammadReza Sadeghi Moghadam

The present study, using genetic algorithm, tries to improve material flow management in supply chain. Consequently, in this paper, an integrated supply-production and distribution planning (SPDP) is considered despite the fact that in most of the Iranian industrial firms, SPDP is done independently. The effective use of integrated SPDP not only enhances the performance rather decreases inventory cost, holding cost, shortage cost and overall supply chain costs. A quantitative mathematical model is used to the problem articulation, and then it is solved by applying heuristic genetic algorithm (GA) method. The proposed model with genetic algorithm could provide the best satisfactory result with the minimum cost. The reliability test was carried by comparing the model results with that of the amount of variables.


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