Research Journal of Applied Sciences, Engineering and Technology 8(6): 687-690, 2014 ISSN: 2040-7459; e-ISSN: 2040-7467 © Maxwell Scientific Organization, 2014 Submitted: June 22, 2013 Accepted: July 05, 2013 Published: August 15, 2014 Corresponding Author: B. Venkat Likhit, SMBS, VIT University, Vellore-632014, Tamil Nadu, India 687 Implementation of Genetic Algorithm in Network Modelling of Multi-level Reverse Logistics for Single Product Siva Prasad Darla, C.D. Naiju, B. Venkat Likhit and Polu Vidya Sagar SMBS, VIT University, Vellore-632014, Tamil Nadu, India Abstract: In this study, a multi level reverse logistics network is developed for a single product. Reverse logistics is a logistic activity beginning from intake of products returned by customers to selling of remanufactured or new products in market; so, it is considered that reverse flow of used products is from various sources like customers, dealers, retailers, manufacturers, etc., to remanufacturer and followed by transportation to secondary market. Due to uncertainties, any traditional supply chain approach to identify potential manufacturing facilities in this situation cannot be employed. Hence, Genetic Algorithm (GA) is used for optimization and minimization of various costs involved in reverse logistics process. A sample numerical data is considered to test performance of the proposed model. Keywords: Cost reduction, network model, optimization, reverse logistics INTRODUCTION Logistics is science of managing flow of goods, energy, information and other resources from source of production to the marketplace. It is difficult to establish any manufacturing and production processes without logistical support. It involves integration of information, transportation, inventory, warehousing, material handling and packaging. Reverse logistics is movement of goods and products from a consumer towards a producer in a channel of distribution. It is the process of planning, implementing, controlling, cost effective flow of raw materials, in-process inventory, finished goods and related information from point of consumption to point of remanufacturing. Sources of reverse logistics may include returned merchandise, excess inventory, outdated products, return due to customer dissatisfaction, etc. It is being practiced in various industries where manufacturing of jet engine components, mobile phones, automotive parts, machine components and refillable containers is happening. The question is whether remanufactured product takes economical and environmental advantage than the disposal of the product. Reverse Logistics are of various types based on product recovery options. They are Reuse, Recycle and Remanufacturing. In reuse, product is used once again rather than disposing it, after cleaning or repairing it. Recycling is the recovery of material without keeping product structure and properties. Different types of materials undergo different recycling processes considering its effects on the environment. Remanufacturing is a concept where used products are completely disassembled by various industrial processes and are resent into different remanufacturing processes. A completely new product might be obtained in this case. In a journal, Automotive remanufacturing: The challenges European remanufacturers are facing, it was reviewed that product take-back has been motivated in the automobile industries, then remanufacturing and redistribution of these products, in form of closed loop supply chain, in the recent years. This study has enumerated the difficulties that the manufacturers were facing and emphasizes on the importance of reducing wastes (Seitz, 2007). Authors of ‘GA model development for reverse logistics’, studied that managing reverse flow of products can be an important potential for winning consumers in future competitive markets. Best solutions are achieved when free space of distribution centers is used for collecting/inspecting used products, especially in cities without recycling/disposal center. GA has given most optimized solution but not the best solution for this problem (Mohammad and Mitra, 2010). A general method based on reverse logistics with aim of reducing aluminium scrap transported between certain productions units of aluminium manufacturing plant. Linear optimization model was used. It was found out that transported products and units that are being processed in-plant have a significant impression on the optimal transport model. The developed model showed that environmental and economic objectives are not always conflicting (Kladivij, 2006). The supply chain efficiency is important to bookstore due to low overall profit margin. A single period model was developed to