J.N. Morse, Reducing the Size of the Nondominated Set: Pruning by Clustering, Computers and Operations Research 7(1-2) (1980) 55--66. Home/Search Document Not in Database Summary Related Articles Check |
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Multiobjective Optimization in Engineering Design: Applications.. - Andersson (2001) (1 citation) (Correct)
....of these methods suffer from a large computational burden. Another disadvantage might be that the decision maker has too many solutions to choose from. There are however methods that support screening of the Pareto set in order to cluster optimal solutions that have similar properties, see Morse [57] and Rosenmann and Gero [71] By sampling a set of discrete points on the Pareto front the decision maker could get a feeling for the form of the front and thereby the possible trade off between the objectives. The simplest way of doing this is to repeatedly change the weightings in a weighted ....
....One way of addressing this problem is to aggregate some objectives, e.g. cost and energy consumption could be aggregated to one overall cost objective. Another possibility is to filter and cluster the solutions so that the set of Pareto optimal solutions is reduced to a set of clusters, see Morse [57] and Rosenmann and Gero [71] Each cluster consists of solutions with similar properties, and therefore the decision maker only has to investigate one solution per cluster. Once the most interesting cluster has been identified, this is where to focus further analysis. Ways to visualize the ....
MORSE J. N., "Reducing the size of the nondominated set: pruning by clustering, " Computers & Operations Research, vol. 7, pp. 55-66, 1980.
Microchannel Optimization Using Multiobjective.. - Sbalzarini, Müller.. (2001) (1 citation) (Correct)
....would probably be biased towards a certain region of the search space, leading to an unbalanced distribution of the solutions. For this work, the average linkage method, a clustering algorithm which has proven to perform well on Pareto optimization, has been chosen. The reader is referred to [Morse (1980)] or [Zitzler Thiele (1999) for details. 5 Strength Pareto Approach with Targeting Compared to other methods like for example the Energy Minimization Evolutionary Algorithm (EMEA) c.f. Jonathan, Zebulum, Pacheco Vellasco (2000) the SPEA has two major advantages: it nds the whole ....
Morse, J. N. 1980 Reducing the size of the nondominated set: Pruning by clustering, Computers and Operations Research, 7 (1-2), 55-66.
Multiobjective Evolutionary Algorithms: A Comparative Case.. - Zitzler, Thiele (1999) (87 citations) (Correct)
....to an unbalanced distribution in the population. Thus, pruning the external nondominated set while maintaining its characteristics might be necessary or even mandatory. A method that has been applied to this problem successfully and studied extensively in the same context is cluster analysis [42][43] In general, cluster analysis partitions a collection of m elements into n groups of relatively homogeneous elements, where n m. The average linkage method [42] a clustering approach that has proven to perform well on this problem (cf. 42] has been chosen in this paper. Step 1: ....
....A method that has been applied to this problem successfully and studied extensively in the same context is cluster analysis [42] 43] In general, cluster analysis partitions a collection of m elements into n groups of relatively homogeneous elements, where n m. The average linkage method [42], a clustering approach that has proven to perform well on this problem (cf. 42] has been chosen in this paper. Step 1: Initialize cluster set C; each external nondominated point i 2 P 0 constitutes a distinct cluster: C = S i ffigg: Step 2: If jCj N 0 , go to Step 5, else go to Step ....
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J. N. Morse, "Reducing the size of the nondominated set: Pruning by clustering," Computers and Operations Research, vol. 7, no. 1-2, pp. 55--66, 1980.
An Evolutionary Algorithm for Multiobjective Optimization.. - Zitzler, Thiele (1998) (91 citations) (Correct)
....set to a manageable size. However, the goal is not only to prune a given set, but rather to generate a representative subset which maintains the characteristics of the original set. Cluster analysis demonstrably fits these requirements and has been successfully applied to this problem (see, e.g. Morse, 1980 ] Rosenman and Gero, 1985 ] In general, cluster analysis partitions a collection of p elements into q groups of relatively homogeneous elements, where q p. Dependent on the working mechanism of the algorithm two forms of clustering are distinguished: direct clustering and hierarchical ....
....and Gero, 1985 ] In general, cluster analysis partitions a collection of p elements into q groups of relatively homogeneous elements, where q p. Dependent on the working mechanism of the algorithm two forms of clustering are distinguished: direct clustering and hierarchical clustering [ Morse, 1980 ] While the first approach sorts the p elements into q groups in one step, the latter works iteratively by joining adjacent clusters until the required number of groups is obtained. Based on numerical experiments Morse [ Morse, 1980 ] compared clustering algorithms of both types in application ....
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J. N. Morse. Reducing the size of the nondominated set: Pruning by clustering. Computers and Operations Research, 7(1-2):55--66, 1980.
An Hybrid Optimization Technique Coupling - Evolutionary And Local (2005) (Correct)
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J.N. Morse, Reducing the Size of the Nondominated Set: Pruning by Clustering, Computers and Operations Research 7(1-2) (1980) 55--66.
Robust Design And Parametric Performance - Study Of An (2005) (Correct)
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J.N. Morse. Reducing the Size of the Nondominated Set: Pruning by Clustering. Computers and Operations Research, 7(1-2), 55--66, 1980.
Unknown - Munich Multi-Objective Optimization (2005) (Correct)
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J.N. Morse. Reducing the Size of the Nondominated Set: Pruning by Clustering. Computers and Operations Research, 7(1-2), 55--66, 1980.
A Comparison of Clustering and Scheduling Techniques for.. - Kianzad, Bhattacharyya (2003) (Correct)
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J. N. Morse. Reducing the size of the nondominated set: Pruning by clustering. Computers and Operations Research, Vol. 7, No. 1-2, 55-66, 1980.
A Survey of Multiobjective Optimization in Engineering Design.. - Andersson (2000) (1 citation) (Correct)
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Morse J. N., "Reducing the size of the nondominated set: pruning by clustering," Computers & Operations Research, vol. 7, pp. 55-66, 1980.
A Thorough Documentation of Obtained Results on Real-Valued.. - Bosman, Thierens (2002) (Correct)
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J. N. Morse. Reducing the size of the nondominated set: Pruning by clustering. Computers and Operations Research, 7(1--2):55--66, 1980.
Evolution Strategies for the Optimization of Microdevices - Müller, Sbalzarini.. (Correct)
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MORSE, J. N. 1980 Reducing the size of the non-dominated set: Pruning by clustering, Computers and Operations Research, 7(1-2), 55-66.
Evolution Strategies for the Optimization of Microdevices - Müller, Sbalzarini.. (Correct)
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MORSE, J. N. 1980 Reducing the size of the non-dominated set: Pruning by clustering, Computers and Operations Research, 7(1-2), 55-66.
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