A Multi-Agent System based simulation approach for planning procurement operations and scheduling with multiple cross-docks. (May 2017)

• Record Type: Journal Article
• Authors: Reddy, Reddivari Himadeep; Kumar, Sri Krishna; Fernandes, Kiran Jude; Tiwari, Manoj Kumar
• Is Part Of: Computers & industrial engineering. Volume 107(2017)
• Page Start: 289
• Page End: 300
• Publication Date: 2017-05
• Subjects: Multi-Agent System -- Maximum Gain Message algorithm -- Improvised Contract Net Protocol -- Task allocation -- Vehicle Routing with Multiple Cross-Docks; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.11.008
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Propose an innovative Multi Agent System (MAS) framework to model procurement operations in India. Exploit Multi Agent System, as a flexible and re-configurable approach to model food supply chains. Focus on strategically locating procurement centers for maximum coverage during. Considers task allocation and optimal routing determination by scheduling agents. Abstract: Reducing food wastage during procurement, collection and storage remain understudied in the context of the developing world that faces unique challenges not seen in the developed world. In order to achieve this objective, a simulation-based framework is needed for evaluation of decision-making policies in procurement context. In this research we propose a Multi-Agent System framework, specifically considering the Indian scenario of paddy procurement operations. We formally define procurement, allocation, milling and scheduling agents under this context and explicitly state the interaction protocols and related algorithms. Procurement agents solve the problem of allocation and maximum coverage to strategically determine their locations. An Improvised Contract Net Protocol is implemented by allocation agents to either reorganize excess procurement quantities among procurement agents or tag to milling agents who implicitly engender disturbance in the system. Scheduling agents solve a Vehicle Routing Problem with Multiple Cross-Docks to determine near optimal routing using a Particle Swarm Optimization Approach. All these agents are entities of a homogeneous system and collectively co-operate and communicate on behalf of a single superior entity. Simulations were performed to identify results such as the percentage of procurement covered, the number of tasks generated, the number of tasks not assigned to any agent.