Managing Green Supply Chain Transportation Operation Using Multi-Agent Framework

Abstract

The concept of software agent has become essential in both artificial intelligence (AI) and mainstream computer science. Multi-agent systems (MAS) provide the way to design and implement information system solutions that exhibit flexibility in a distributed environment. Simulation plays a crucial role in analyzing MAS solutions' behaviour during the automated software solution analysis and design phase. This chapter uses the idea of multi-agent computing and provides a software framework for green supply chain management, carbon footprint assessment planning for a multimodal transportation scenario. In this framework, the software agents' operational activities managed with the help of a hybrid knowledge-based system that uses rule-based reasoning (RBR) and case-based reasoning (CBR). The presented framework accepts a transport logistic service request and creates a transport plan that helps optimize environmental impact (i.e., CO2 footprint) by retrieving best practices (i.e., carbon footprint perspective) for each route from a repository of best-practiced cases.