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Journal of Environmental
Informatics
Online ISSN
1684-8799 / Print ISSN 1726-2135
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© 2007 ISEIS.
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A Goal Programming Based Multi-Time Step Optimal Material Flow Analysis Model for Integrated Computer Waste Management
P. K. Ahluwalia* and A. K. Nema
Department of Civil Engineering, I.I.T. Delhi, New Delhi 110016, India
*Corresponding author. Email: poonamkahluwalia@yahoo.co.in
Abstract
Management of computer waste is a growing concern and is more serious in developing countries where rudimentary methods of reuse, recovery and disposal are in frequent use which poses grave environmental and health hazards. Hence there is a clear reason to be concerned about the management scheme for computer waste which will be cost effective and also environmentally friendly. However, assessment of risk from the management of computer waste is a difficult task due to uncertainty in exact composition of toxic constituents and their release mechanism in the environment. The present study attempts to assess the risk associated with various computer waste management activities in relative terms and presents an integer linear goal programming based multi time step optimal material flow analysis model to achieve satisfaction of multiple objectives of economy and health and environmental risk. The model selects various treatment and disposal facilities from a given set and allocates optimum quantities of waste to them along chosen transportation routes, depending on different priorities to cost and risk. An illustrated hypothetical example of computer waste management is presented to demonstrate the usefulness of the proposed formulation. Uncertainty in the waste generation quantities has been addressed using Monte Carlo simulation.
Keywords: computer waste, goal programming, integrated waste management, Monte Carlo simulation, multi-objective optimization, optimal material flow
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Cite this paper as: P. K. Ahluwalia and A. K. Nema, 2007. A Goal Programming Based Multi-Time Step Optimal Material Flow Analysis Model for Integrated Computer Waste Management. Journal of Environmental Informatics, 10(2), 82-98. http://dx.doi.org/10.3808/jei.200700103
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