Obayashi, S., S. Takahashi, and Y. Takeguchi, " Niching and elitist models for mogas" In A. E. Eiben, T. Bck, M. Schoenauer, and H.P.Schwefer(editors), 5 International Conference on Parallel Problem Solving from Nature (PPSN-V), Berlin, Germany, pp.260-269.Springer.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....Our results on a real data set show that our approach is easier to interpret and more accurate than the traditional method used in marketing. 1 Introduction In the last decade, evolutionary multi objective (EMO) algorithms have been applied to solve many engineering and scientific problems [20, 10, 16, 3]. In multi objective optimization problems, we expect a set of optimal solutions rather than a single optimal solution because each solution should be evaluated on multiple objectives and often such objectives are in conflict with each other. In particular, we are interested in finding a ....

S. Obayashi, S. Takahashi, and Y. Takeguchi. Niching and elitist models for MOGAs. In 5th Int'l Conf. on Parallel Problem Solving from Nature (PPSN-V), pages 260--269, Berlin, Germany, 1998. Springer.

....selection of the sharing factor. MOGA has been a very popular EMOO technique (particularly within the control community) and it normally exhibits a very good overall performance [11] 4.3. 2 Some Applications Fault diagnosis [45] Control system design [3, 69, 21] Wing planform design [48]. Design of multilayer microwave absorbers [68] 4.4 NSGA The Nondominated Sorting Genetic Algorithm (NSGA) was proposed by Srinivas and Deb [60] and is based on several layers of classi cations of the individuals. Before selection is performed (stochastic remainder proportionate selection ....

S. Obayashi, S. Takahashi, and Y. Takeguchi. Niching and Elitist Models for MOGAs. In A. E. Eiben, M. Schoenauer, and H.-P. Schwefel, editors, Parallel Problem Solving From Nature | PPSN V, pages 260-269, Amsterdam, Holland, 1998. Springer-Verlag.

....more that just one aspect, it is very difficult to identify the features which are mainly responsible for the better performance of one algorithm over another. On the contrary, a few other studies take one algorithm and focus on a specific operator or parameter to tune, e.g. the selection method [10, 12]. In this case the results are valid for the algorithm under concern and highly dependent on the other algorithmic parameters. Hence, it has remainedopenuptonow how a certain parameter or a certain operator affects the overall performance independent of the specific implementation and the ....

....during the run, but in most cases it just contains non dominated solutions and therefore approximates the Pareto set. If the archived solutions reproduce as well, we say the algorithm uses elitism. Recent studies suggest that the use of elitism improves multi objective evolutionary algorithms [10, 12, 18]. Another issue is the assignment of fitness values to the individuals. In this study we concentrate on Pareto based methods because of their acknowledged advantages over aggregation and population based methods [5] Different techniques inferring a scalar value from the partially ordered ....

S. Obayashi, S. Takahashi, and Y. Takeguchi. Niching and elitist models for MOGAs. In A. E. Eiben et al., editor, Parallel Problem Solving from Nature -- PPSN V, pages 260--269, Berlin, 1998. Springer.

.... on and UrestiCharre, 1997; Fonseca and Fleming, 1998; Parks and Miller, 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Van Veldhuizen and Lamont, 1998a; Rudolph, 1998) niching (Obayashi et al. 1998), and elitism (Parks and Miller, 1998; Obayashi et al. 1998) while others have concentrated on developing new evolutionary techniques (Laumanns et al. 1998; Zitzler and Thiele, 1999) For a thorough discussion of evolutionary algorithms for multiobjective optimization, the interested reader is ....

.... and Miller, 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Van Veldhuizen and Lamont, 1998a; Rudolph, 1998) niching (Obayashi et al. 1998) and elitism (Parks and Miller, 1998; Obayashi et al. 1998), while others have concentrated on developing new evolutionary techniques (Laumanns et al. 1998; Zitzler and Thiele, 1999) For a thorough discussion of evolutionary algorithms for multiobjective optimization, the interested reader is referred to Fonseca and Fleming (1995) Horn (1997) Van ....

Obayashi, S., Takahashi, S. and Takeguchi, Y. (1998). Niching and elitist models for mogas. In Eiben, A. E., B ack, T., Schoenauer, M. and Schwefel, H.-P., editors, Fifth International Conference on Parallel Problem Solving from Nature (PPSN-V), pages 260--269, Springer, Berlin, Germany.

.... and Uresti Charre 1997; Fonseca and Fleming 1998; Parks and Miller 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Veldhuizen and Lamont 1998a; Rudolph 1998) niching (Obayashi, Takahashi, and Takeguchi 1998), and elitism (Parks and Miller 1998; Obayashi, Takahashi, and Takeguchi 1998) while others have concentrated on developing new evolutionary techniques (Laumanns, Rudolph, and Schwefel 1998; Zitzler and Thiele 1999) For a thorough discussion of evolutionary algorithms for multiobjective ....

.... 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Veldhuizen and Lamont 1998a; Rudolph 1998) niching (Obayashi, Takahashi, and Takeguchi 1998) and elitism (Parks and Miller 1998; Obayashi, Takahashi, and Takeguchi 1998), while others have concentrated on developing new evolutionary techniques (Laumanns, Rudolph, and Schwefel 1998; Zitzler and Thiele 1999) For a thorough discussion of evolutionary algorithms for multiobjective optimization, the interested reader is referred to (Fonseca and Fleming 1995; Horn ....

Obayashi, S., S. Takahashi, and Y. Takeguchi (1998). Niching and elitist models for mogas. In A. E. Eiben, T. Back, M. Schoenauer, and H.-P. Schwefel (Eds.), Fifth International Conference on Parallel Problem Solving from Nature (PPSN-V), Berlin, Germany, pp. 260-269. Springer.

....On the whole, these algorithms are based on either of the mentioned established algorithms with problem specific enhancements. Examples can be found in (Todd Sen, 1997) Obayashi, Tsukahara, Nakamura, 1997) Cunha, Oliviera Covas, 1997) and (Loughlin Rajithan, 1997) Recently Shigura (Obayashi, Takahashi Takeguchi, 1998) compared several sharing schemes in multiobjective evolutionary optimisation, including Coevolutionary Shared Niching, which is implemented in the algorithm that will be described in the next section. A comprehensive overview of evolutionary approaches to multiobjective optimisation can be found ....

Obayashi, S. Takahashi, and Y. Takeguchi. Niching and Elitist Models for MOGAs, In A. E. Eiben, M. Schoenauer, and H.-P. Schwefel, editors, Parallel Problem Solving From Nature -- PPSN V, pages 260-269, Amsterdam, Holland, 1998.

....whereas other algorithms do not use any such mechanism. Nevertheless, an interesting aspect of that study is that it shows the importance of introducing elitism in evolutionary multi criterion optimization. Similar effect of elitism in multi criterion optimization was also observed elsewhere [25]. 3.5 Srinivas and Deb s non dominated sorting genetic algorithm (NSGA) Using the concept of sharing functions, Srinivas and Deb [32] have implemented Goldberg s idea most directly. The idea behind NSGA is that a ranking selection method is used to emphasize current nondominated points and ....

Obayashi, S., Takahashi, S., and Takeguchi, Y. (1998). Niching and elitist models for MOGAs. Parallel Problem Solving from nature, V, 260--269.

.... and Uresti Charre 1997; Fonseca and Fleming 1998b; Parks and Miller 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Veldhuizen and Lamont 1998; Rudolph 1998) niching (Obayashi, Takahashi, and Takeguchi 1998), and elitism (Parks and Miller 1998; Obayashi, Takahashi, and Takeguchi 1998) while others have concentrated on developing new evolutionary techniques (Laumanns, Rudolph, and Schwefel 1998; Zitzler and Thiele 1998a) In spite of this variety, there is a lack of studies which compare the ....

.... 1998) In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto optimal front (Veldhuizen and Lamont 1998; Rudolph 1998) niching (Obayashi, Takahashi, and Takeguchi 1998) and elitism (Parks and Miller 1998; Obayashi, Takahashi, and Takeguchi 1998), while others have concentrated on developing new evolutionary techniques (Laumanns, Rudolph, and Schwefel 1998; Zitzler and Thiele 1998a) In spite of this variety, there is a lack of studies which compare the performance and different aspects of the several approaches. Consequently, the ....

Obayashi, S., S. Takahashi, and Y. Takeguchi (1998). Niching and elitist models for mogas. In Fifth International Conference on Parallel Problem Solving from Nature (PPSN-V), pp. 260--269.

....whereas other algorithms do not use any such mechanism. Nevertheless, an interesting aspect of that study is that it shows the importance of introducing elitism in evolutionary multi criterion optimization. Similar effect of elitism in multi criterion optimization was also observed elsewhere [30]. 1.4.5 Srinivas and Deb s non dominated sorting genetic algorithm (NSGA) Srinivas and Deb [38] have implemented Goldberg s idea most directly. The idea behind NSGA is that a ranking selection method is used to emphasize current non dominated points and a niching method is used to maintain ....

....1997 Aerodynamic shape design [33, 32] E. Zitzler and L. Thiele 1998 Synthesis of digital hardwaresoftware multi processor system [45] G. T. Parks and I. Miller 1998 Pressurized water reactor reload design [31] S. Obayashi, S. Takahashi, and Y. Takeguchi 1998 Aircraft wing planform shape design [30] K. Mitra, K. Deb, and S. K. Gupta 1998 Dynamic optimization of an industrial nylon 6 semibatch reactor [29] D. Cvetkovic and I. Parmee 1998 Airframe design [5] 1.8 SUMMARY In this paper, we have discussed evolutionary algorithms for multi criterion optimization. By reviewing a couple of popular ....

Obayashi, S., Takahashi, S., and Takeguchi, Y. (1998). Niching and elitist models for MOGAs. Parallel Problem Solving from nature, V, 260--269.

....are desired: 1) the solutions obtained are Pareto optimal, and 2) they are uniformly sampled from the Pareto optimal set. To achieve these, MOGA s have been introduced successfully in [2] Furthermore, it was shown that the so called best selection helps to find the extreme Pareto solutions [3]. This form of selection picks up the best individuals among parents and children for the next generation in a manner similar to CHC [4] The extreme Pareto solutions are the optimal solutions of the single objectives. By examining the extreme Pareto solutions, the quality of Pareto solutions can ....

S. Obayashi, S. Takahashi, and Y. Takeguchi, "Niching and elitist models for MOGAs," in Parallel Problem Solving from Nature---PPSN V. Berlin, Germany: Springer, 1998, pp. 260--269. (Lecture Notes in Computer Science).

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Obayashi, S., S. Takahashi, and Y. Takeguchi, " Niching and elitist models for mogas" In A. E. Eiben, T. Bck, M. Schoenauer, and H.P.Schwefer(editors), 5 International Conference on Parallel Problem Solving from Nature (PPSN-V), Berlin, Germany, pp.260-269.Springer.

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