Due to the implementation of government legislation, social
responsibility, environmental concern, economic benefits and customer
awareness the industries are under a great pressure not only to provide
environmentally friendly products but also to take back the product after
its use. The issue in reverse logistics is to take back the used products,
either under warranty or at the end of use or at the end of lease, so that
the products or its parts are appropriately disposed, recycled, reused or
remanufactured. In order to overcome this issue, it is necessary to setup a
logistics network for arising goods flow from end users to manufacturers.
In this study, the optimum usage of secondary lead recovered from the spent
lead-acid batteries for producing new battery is presented. The disposal in
surface or sewage water or land of liquid content of the lead-acid
batteries is strictly restricted. Because of the need for environmental
protection and the lack of considerable lead resources, the spent batteries
treatment and lead recovery are becoming crucial now-a-days. The objective
of this paper is to develop a multi echelon, multi period, multi product
closed loop supply chain network model for product returns and the
decisions are made regarding material procurement, production,
distribution, recycling and disposal. The proposed heuristics based genetic
algorithm (GA) is applied as a solution methodology to solve mixed integer
linear programming model (MILP). Finally the computational results obtained
through GA are compared with the solutions obtained by GAMS optimization
software. The solution reveals that the proposed methodology performs very
well in terms of both quality of solutions obtained and computational time.
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