A Multi Agent-Based Approach for Supply Chain Network

2010 ◽  
Vol 136 ◽  
pp. 82-85
Author(s):  
Rui Wang

This paper applies the multi-agent system paradigm to collaborative negotiation in supply chain network. Multi-agent computational environments are suitable for dealing with a class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving agents. An evolution teamwork system based on multi-agents that can organize most team members in supply chain network was proposed. The proposed model performs adaptive development relying on differential evolution process. The experimental results show that our developing teamwork system is able to provide the adaptability of team differential evolution is global optimization and continuously develop teamwork members for the resources management in supply chain network.

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.


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.


2021 ◽  
pp. 0734242X2199466
Author(s):  
Naeme Zarrinpoor

This paper aims to design a supply chain network for producing double glazed glass from the recycling of waste glass. All three pillars of sustainability are taken into consideration. The economic objective tries to maximize total profits. The environmental objective considers the energy consumption, the generated waste, the greenhouse gas emission, the water consumption, and the fuel consumption of vehicles. The social objective addresses created job opportunities, the worker safety, the regional development, the worker benefit, and training hours. To solve the model, a two-stage framework based on the group best-worst method and an interactive fuzzy programming approach is developed. The proposed model is validated through a real case study based on waste glass management in the city of Shiraz. It is revealed that when sustainable development goals are approached, a great degree of improvement will be attained in environmental and social aspects without a significant decrease in the economic sustainability. The results also demonstrate that the locations of glass recycling centres are different under economic, environmental, and social pillars, and the proposed model yields an optimal system configuration with a proper satisfaction degree of all objectives. Moreover, applying the proposed solution procedure enables system designers to obtain the most desirable trade-off between different aspects of sustainability.


2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat

Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.


2021 ◽  
Author(s):  
Fatemeh Mohebalizadehgashti

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this thesis, environmental concerns with a mathematical model are investigated to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. A multi-objective mixed-integer linear programming formulation is developed to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization. To demonstrate the efficiency of the proposed optimization model, a green meat supply chain network for Southern Ontario, Canada is designed. A solution approach based on augmented εε-constraint method is developed for solving the proposed model. As a result, a set of Pareto-optimal solutions is obtained. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature. Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented εε-constraint.


2020 ◽  
Author(s):  
Wided Ali ◽  
Fatima Bouakkaz

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.


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