Abstract
Sustainable economic development requires the inclusion of environmental factors in the decision making procedure. The generic objective of the Environmentally Sensitive Investment System (ESIS) Project is to provide industry and governmental departments or agencies with a tool to assess the technical and economic implications of capital-intensive projects, in response to stated environmental policies. More specifically, the ESIS prototype helps to find wastewater management alternatives that meet given environmental regulatory standards in a technologically sound and cost-efficient manner. The use of this decision support system will enhance the ability of managers and planners to explore the quantitative implications of a wide range of options. ESIS incorporates a combination of artificial intelligence and operations research techniques, database management and visualization tools, integrated under a graphical user interface. The ESIS prototype runs on top-of-the-line personal computers.
Similar content being viewed by others
References
J.G. Boon, J. Pintér and L. Somlyódy, A new stochastic approach for controlling point source river pollution, in:Proceedings of the Baltimore IAHS Symposium, IAHS Publication No. 180 (International Association of Hydrologic Sciences, London, 1989) pp. 141–149.
Environment Canada, Cleaning up pollution in the pulp and paper industry: An overview of the federal regulatory strategy, Working Document, Ottawa, Ont. (1990).
Environment Canada, Regulations for the Canadian pulp and paper industry, Proposed legislation, Ottawa, Ont. (1992).
Canadian Pulp and Paper Association, A statement by the pulp and paper industry — solid waste management, CPPA, Montreal, Que. (1991).
A.G. Colodey and P.G. Wells, Effects of pulp and paper mill effluents on estuarine and marine ecosystems in Canada: A review, J. Aquatic Ecosyst. Health 1(1992)201–226.
K. Fedra, Smart software for water resources planning and management, in:Decision Support Systems, ed. D.P. Loucks and J.R. Da Costa, NATO ASI Series Vol. G 26 (Springer, Berlin, 1991) pp. 145–172.
M. Fels and D.S. Lycon, ESIS project: Waste water treatment modules, Department of Chemical Engineering, Technical University of Nova Scotia, Halifax, N.S. (1992).
A. Fiacco and G.P. McCormick,Nonlinear Programming: Sequential Unconstrained Minimization Techniques (Wiley, New York, 1968).
R. Fletcher, Penalty functions, in:Mathematical Programming: The State of the Art, ed. A. Bachem, M. Grötschel, and B. Korte (Springer, Berlin, 1983) pp. 87–114.
J. Galambos,The Asymptotic Theory of Extreme Order Statistics (Wiley, New York, 1978).
R. Horst and H. Tuy,Global Optimization: Deterministic Approaches (Springer, Berlin, 1990).
D.C.L. Lam and D.A. Swayne, Integrating database, spreadsheet, graphics, GIS, statistical simulation models and expert systems: Experiences with the RAISON system on microcomputers, in:Decision Support Systems, ed. D.P. Loucks and J.R. Da Costa, NATO ASI Series, Vol. G 26 (Springer, Berlin, 1991) pp. 429–459.
A. Lewandowski and A.P. Wierzbicki,Aspiration-Based Decision Support Systems (Springer, Berlin, 1989).
D.S. Lycon, Sensitivity analysis of wastewater treatment models, ESIS Project Technical Note, School for Resource and Environmental Studies, Dalhousie University, Halifax, N.S. (1992).
McCubbin Consultants, Inc., Best available technology for the Ontario pulp and paper industry, Report prepared for the Ontario Ministry of Environment, Toronto, Ont. (1992).
Ontario Waste Management Corporation, Industrial waste audit and reduction manual, OWMC Toronto, Ont. (1989).
G.G. Patry and D.T. Chapman (eds.),Dynamic Modelling and Expert Systems in Wastewater Engineering (Lewis, Chelsea, MI, 1989).
J. Pintér, Branch-and-bound methods for solving global optimization problems with Lipschitzian structure, Optimization 19(1988)101–110.
J. Pintér, Stochastic modelling and optimization for environmental management, Ann. Oper. Res. 31(1991)527–544.
J. Pintér, Lipschitzian global optimization: Some prospective applications, in:Recent Advances in Global Optimization, ed. C.A. Floudas and P.M. Pardalos (Princeton University Press, Princeton, NJ, 1992). pp. 399–432.
J. Pintér, Convergence qualification of adaptive partition algorithms in global optimization, Math. Progr. 56(1992)343–360.
J. Pintér, and D.S. Lycon, Approximating TOX as a function of TSS and BOD, ESIS Project Technical Note, School for Resource and Environmental Studies, Dalhousie University, Halifax, N.S. (1992).
J. Pintér and D.S. Lycon, Statistical uncertainty analysis of wastewater treatment systems, ESIS Project Technical Note, School for Resource and Environmental Studies, Dalhousie University, Halifax, N.S. (1992).
J. Pintér, ESIS project: Final report, School for Resource and Environmental Studies, and School of Business Administration, Dalhousie University, Halifax, N.S. (1993).
United States Environmental Protection Agency, Waste minimization opportunity assessment manual, EPA Report No. 625/7-88/003, Cincinnati, OH (1988).
R. Wets, Stochastic programming: Solution techniques and approximation schemes, in:Mathematical Programming: The State of the Art, ed. A. Bachem, M. Grötschel and B. Korte (Springer, Berlin, 1983) pp. 566–603.
A.A. Zhigljavsky,Theory of Global Random Search (Kluwer, Dordrecht, 1991).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Pintér, J., Fels, M., Lycon, D.S. et al. An intelligent decision support system for assisting industrial wastewater management. Ann Oper Res 58, 455–477 (1995). https://doi.org/10.1007/BF02032381
Issue Date:
DOI: https://doi.org/10.1007/BF02032381