The past decade has seen a considerable development of techniques designed to help decision makers faced with problems involving conflicting objectives. In particular, a family of methods known collectively as interac...
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The past decade has seen a considerable development of techniques designed to help decision makers faced with problems involving conflicting objectives. In particular, a family of methods known collectively as interactive multi-objective programming has come to the fore. This paper presents the underlying rationale of such methods, albeit as seen by a devil's advocate, briefly surveys some areas of application, but then questions the validity of these methods because their assumptions are not supported by the empirical results of behavioural decision theory.
The traditional data envelopment analysis (DEA) model does not include a decision maker's (DM) preference structure while measuring relative efficiency, with no or minimal input from the DM. To incorporate DM'...
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The traditional data envelopment analysis (DEA) model does not include a decision maker's (DM) preference structure while measuring relative efficiency, with no or minimal input from the DM. To incorporate DM's preference information in DEA, various techniques have been proposed. An interesting method to incorporate preference information, without necessary prior judgment, is the use of an interactive decision making technique that encompasses both DEA and multi-objective linear programming (MOLP). In this paper, we will use Zionts-Wallenius (Z-W) method to reflecting the DM's preferences in the process of assessing efficiency in the general combined-oriented CCR model. A case study will conducted to illustrate how combined-oriented efficiency analysis can be conducted using the MOLP method. (C) 2009 Elsevier B.V. All rights reserved.
In this paper a problem of air pollution control is studied, posing it as a multi-objective control problem of partial differential equations. The original problem, dealing with the optimal management of a set of indu...
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In this paper a problem of air pollution control is studied, posing it as a multi-objective control problem of partial differential equations. The original problem, dealing with the optimal management of a set of industrial plants inside a populated area, is formulated by means of the diffusion transport equation, including a linear reaction term and source terms modelled by Dirac deltas. Introducing adjoint state techniques, the problem transforms into a problem of multi-objective optimization in Banach spaces, where the large number of objective functions discourages the complete search of its Pareto front. Therefore, in order to solve the problem, two interactive methods of multi-objectiveprogramming are proposed: the VIA and the STEM algorithms. Finally, the paper illustrates how to combine both algorithms to solve in a more effective way a realistic problem posed in the Metropolitan Area of Guadalajara (Mexico).
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