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An Intelligent Multi-Agent Based Model for Collaborative Logistics Planning


An Intelligent Multi-Agent Based Model for Collaborative Logistics Planning

Khayyat, Manal (2015) An Intelligent Multi-Agent Based Model for Collaborative Logistics Planning. Masters thesis, Concordia University.

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Efficient freight distribution is indispensable for sustaining customer demand in modern times. In recent years, there has been a steady growth in the use of information systems in the logistics domain towards facilitating an agile distribution process. This study investigates the problem of collaboration planning in logistics and proposes an agent based approach for better management of collaborative logistics. Based on the approach, a decision support system is designed that utilizes RFID technology for ensuring inventory accuracy and monitoring carriers’ delivery movements.

The proposed approach involves three steps. In the first step, a conceptual framework is designed. Afterwards, a simulation agent based model is developed including six autonomous agents namely (RFIDG, Supplier, Retailer, Carrier, Network, and City Administrator) interacting with each other, as well as, with the surrounding environment. In the second step, game theory is utilized to study and analyze suppliers’ collaboration and carriers’ collaboration behavior in detail. Modeled games are solved using Nash Equilibrium. Finally, correctness of the games is verified by formulating them mathematically. Developed optimization equations are fundamental to the operations research field. They employ the simplex and goal algorithms of linear programming.

Results prove that there are plethora of advantages such as automatism and real time response, cost reduction, increased suppliers’ profits, time management, and a collaborative framework for implementing the proposed agent based model where suppliers, retailers, and carriers will receive immediate benefits. Major contributions of the thesis stems from considering future technologies such as RFID and agent oriented strategies to provide fast quality services to customers.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Item Type:Thesis (Masters)
Authors:Khayyat, Manal
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Quality Systems Engineering
Date:February 2015
Thesis Supervisor(s):Awasthi, Anjali
Keywords:Agent based model, decision support system, game theory, less than truck load, linear programming, supply chain management.
ID Code:979728
Deposited On:13 Jul 2015 14:00
Last Modified:18 Jan 2018 17:49
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