Authors:
Carman Ka Man Lee
1
;
Tan Wil Sern
1
and
Eng Wah Lee
2
Affiliations:
1
Nanyang Technological University, Singapore
;
2
Singapore Institute of Manufacturing Technology, Singapore
Keyword(s):
Reverse Logistics, Radio Frequency Identification (RFID), Genetic Algorithm, Location determination.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
Abstract:
Recently, reverse logistics management has become an integral part of the business cycle. This is mainly due to the need to be environmental friendly and urgent need to reuse scarce resources. Traditionally, reverse logistics activities have been a cost center for most businesses without generating extra revenue. However, due to recent increase in commodity and energy prices, reverse logistics management could eventually be a cost savings method. In this research, we propose using Radio Frequency Identification (RFID) technology to better optimize and streamline reverse logistics operations. Using RFID, we try to eliminate parts of the unknowns in reverse logistics flow that made reverse logistics model complicated. Furthermore, Genetic algorithm is used to optimize the place of initial collection center so as to cover the largest population possible in order to reduce logistics cost and provide convenience to end users. This study is based largely on literature review of past workin
gs and also experiments are conducted on RFID hardware to test for its suitability. The significance of this paper is to adopt ubiquitous RFID technology and Genetic Algorithms for reverse logistics so as to obtain an economic reverse logistics network.
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