Wienke, D., Lucasius, C., and Kateman, G. (1992). Multicriteria target vector optimization of analytical procedures using a genetic algorithm. Part I. Theory, numerical simulations and application to atomic emission spectroscopy. Analytica Chimica Acta, 265(2):211--225.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....in objective space, where w j is often set to k g j k [47] This technique can be used in fitness proportional, tournament, or rank based selection. Table 5 lists the known minimax MOEA techniques. Table 5: Minimax Techniques Approach Description Application Objectives (#) Chromosome GA [159] 3 (1993) Goal attainment; Population monitored for nondominated solutions Unknown Unknown Unknown GA [24] 1995) Tchebycheff weighting, Uniformly varies key parameter Groundwater contanimant monitoring (2) Undetected plumes; Contaminated area Fixed length integer string GA [25] ....

Wienke, Dietrich, et al. "Multicriteria Target Vector Optimization of Analytical Procedures Using a Genetic Algorithm," Analytica Chimica Acta, 265 :211--225 (1992).

....Although much of this theory is (may be ) valid when regarding MOEAs, some is not. Thus, current knowledge concerning selected MOEA theoretical issues is now discussed. 5.1.1 Fitness Functions The general manner of fitness function implementation is two fold. This is reflected by the work of Wienke et al. 1992) and Fonseca and Fleming (1997b) who each solved MOPs with seven fitness functions. Wienke et al. essentially, used seven copies of an identical objective function, that of meeting atomic emission intensity goals for seven different elements. Although the elements and associated goals are each ....

Wienke, D., Lucasius, C. and Kateman, G. (1992). Multicriteria Target Vector Optimization of Analytical Procedures Using a Genetic Algorithm. Analytica Chimica Acta, 265:211--225.

....new runs of the optimizer may be required until a suitable solution is found. Several applications of evolutionary algorithms in the optimization of aggregating functions have been reported in the literature, from the simple weighted sum approach (Jakob et al. 1992) to target vector optimization (Wienke et al. 1992). Goal attainment, among other methods, was used by Wilson and Macleod (1993) who also monitored the population for non dominated solutions. Handling constraints with penalty functions is yet another example of an additive aggregating function. The fact that penalty functions are generally ....

Wienke, D., Lucasius, C., and Kateman, G. (1992). Multicriteria target vector optimization of analytical procedures using a genetic algorithm. Part I. Theory, numerical simulations and application to atomic emission spectroscopy. Analytica Chimica Acta, 265(2):211--225.

....provide valuable alternatives [12, 13] However, since the algorithm sees such alternatives as sub optimal, they cannot be expected to be optimal in any sense. Aggregating functions have been widely used with EAs, from the simple weighted sum approach, e.g. 14] to target vector optimization [15]. An implementation of goal attainment, among other methods, was used by Wilson and Macleod [12] 4.2.1 Non Pareto approaches Treating objectives separately was first proposed by Schaffer [16] as a move towards finding multiple non dominated solutions with a single algorithm run. In his ....

D. Wienke, C. Lucasius, and G. Kateman, "Multicriteria target vector optimization of analytical procedures using a genetic algorithm. Part I. Theory, numerical simulations and application to atomic emission spectroscopy," Analytica Chimica Acta, vol. 265, no. 2, pp. 211--225, 1992.

....in the literature. A number of authors (Syswerda and Palmucci, 1991; Jakob et al. 1992; Jones et al. 1993) provide examples of the use of the popular weighted sum approach. Using target vector optimization, which consists of minimizing the distance in objective space to a given goal vector, Wienke et al. 1992) report work on a problem in atomic emission spectroscopy. Goal attainment (Gembicki, 1974) a related technique which seeks to minimize the weighted difference between objective values and the corresponding goals, was used amongst other methods by Wilson and Macleod (1993) who also monitored the ....

Wienke, D., Lucasius, C., and Kateman, G. (1992). Multicriteria target vector optimization of analytical procedures using a genetic algorithm.

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Wienke, D., Lucasius, C., and Kateman, G. (1992). Multicriteria target vector optimization of analytical procedures using a genetic algorithm. Part I. Theory, numerical simulations and application to atomic emission spectroscopy. Analytica Chimica Acta, 265(2):211--225.

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