Abstract
The introduction of best available techniques (BAT) with the European Commission's directive 96/61, created a new framework for ‘cleaner’ production in the industrial sector. BATs practically constitute recommended techniques for each of the steps in the manufacturing process. Thus, the industries must decide on which BATs are most appropriate for their processes. In the current study, an integrated approach is applied in order to find the mixture of BATs for the entire industrial sector that satisfies as much as possible the economic and the environmental criteria. The former represent the industry owner's point of view expressed by the Net Present Value of the projects and the latter represent the society's point of view quantified by the emission reduction in some major pollutants. The developed multi-objective optimization model is addressed using two methods: (1) goal programming and (2) generation of the Pareto optimal solutions using an augmented version of the ε-constraint method followed by an interactive filtering process in order to select the most preferred Pareto optimal solution. The generation of the Pareto optimal solutions is performed using an improved version of the widely used ε-constraint method that overcomes some of its known drawbacks. The COMBAT tool (combinatorial optimization with multiple criteria for BAT selection) that is developed for implementing these methods is also described and the results from its application in the industrial sector of the greater Athens area are presented.
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References
Belton V and Stewart TJ (2002). Multiple Criteria Decision Analysis. An Integrated Approach. Kluwer Academic Publishers: London.
Brooke A, Kendrick D, Meeraus A and Raman R (1998). GAMS. A User's Guide. GAMS Development Corporation: Washington.
Chankong V and Haimes YY (1983). Multiobjective Decision Making: Theory and Methodology. North-Holland: New York.
Cohon JL (1978). Multiobjective Programming and Planning. Academic Press: New York.
Ehrgott M and Ryan DM (2002). Constructing robust crew schedules with bicriteria optimization. J Multi-Crit Decis Anal 11: 139–150.
Ehrgott M and Wiecek M (2005). Multiobjective programming. In: Figueira J., Greco S. and Ehrgott M. (eds). Multiple Criteria Decision Analysis: State of the Art Surveys. Springer: Berlin, pp. 667–722.
EIPPCB — European Integrated Pollution Prevention and Control Bureau (2006). Reference document on Economics and Cross-Media effects. Available at http://eippcb.jrc.es/pages/FActivities.htm, accessed 11 January 2008.
Georgopoulou E, Lalas DP and Papagiannakis L (1997). A multicriteria decision aid approach for energy planning problems: The case of renewable energy option. Eur J Opl Res 103: 38–54.
Georgopoulou E, Sarafidis Y, Mirasgedis S, Zaimi S and Lalas DP (2003). A multiple criteria decision-aid approach in defining national priorities for greenhouse gases emissions reduction in the energy sector. Eur J Opl Res 146: 199–215.
Hwang CL and Masud A (1979). Multiple Objective Decision Making Methods and Applications: A State of the Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 164. Springer-Verlag: Berlin.
Ignizio JP (1982). Linear Programming in Single- & Multiple-Objective Systems. Prentice-Hall: Englewood Cliffs, NJ.
Isermann H and Steuer RE (1987). Computational experience concerning payoff tables and minimum criterion values over the efficient set. Eur J Opl Res 33: 91–97.
Jones DF and Tamiz M (2002). Goal programming in the period 1990–2000. In: Ehrgott M. and Gandibleux X. (eds). Multiple Criteria Optimization. Kluwer Academic Publishers: Boston, pp. 129–170.
Lahdelma R, Salminen P and Hokkanen J (2002). Locating a waste treatment facility by using stochastic multicriteria acceptability analysis with ordinal criteria. Eur J Opl Res 142: 345–356.
Mavrotas G (2007). Generation of efficient solutions in multiobjective mathematical programming problems using GAMS. Effective implementation of the ε-constraint method. Report paper available at http://www.gams.com/modlib/libhtml/epscm.htm, accessed on 25th August 2007.
Mavrotas G, Ziomas Y and Diakoulaki D (2006). A combined MOIP — MCDA approach to building and screening atmospheric pollution control strategies in urban regions. Environ Mngt 38: 149–160.
Miettinen KM (1998). Nonlinear Multiobjective Optimization. Kluwer Academic Publishers: Boston.
National Observatory of Athens, EPEM SA, LDK Ltd. (2006). Decision Aid Framework for the assessment of impacts from the introduction of Best Available Techniques in industry (DAF-BAT). Executive summary (in English), available at http://www.epem.gr/daf-bat/index.htm.
Reeves GR and Reid RC (1988). Minimum values over the efficient set in multiple objective decision making. Eur J Opl Res 36: 334–338.
Romero C (1996). Multicriteria decision analysis and environmental economics: An approximation. Eur J Opl Res 96: 81–89.
Steuer RE (1989). Multiple Criteria Optimization. Theory, Computation and Application, 2nd ed., Krieger: Malabar, FL.
Steuer RE (1997). Non-fully resolved questions about the efficient/nondominated set. In: Climaco J. (ed). Multicriteria Analysis. Springer: Berlin, pp. 585–589.
Tamiz M and Jones DF (1997). Interactive framework for investigation of goal programming models: Theory and practice. J Multi-Crit Decis Anal 6: 52–60.
Tamiz M, Jones D and Romero C (1998). Goal programming for decision making: An overview of the current state of the art. Eur J Opl Res 111: 569–581.
Zeleny M (1981). The pros and cons of goal programming. Comput Opns Res 8: 357–359.
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Mavrotas, G., Georgopoulou, E., Mirasgedis, S. et al. Multi-objective combinatorial optimization for selecting best available techniques (BAT) in the industrial sector: the COMBAT tool. J Oper Res Soc 60, 906–920 (2009). https://doi.org/10.1057/palgrave.jors.2602618
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DOI: https://doi.org/10.1057/palgrave.jors.2602618