A real-coded niching memetic algorithm for continuous multimodal function optimization

Vitela, Javier E.; Castaños, Octavio

doi:10.1109/cec.2008.4631087

Cited by 22 publications

(17 citation statements)

References 12 publications

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“…In addition to the methods listed above, there are niching methods such as sequential niching [2,53], the GAS (S stands for species) method [26], species competition [30,24,25,58], localized niching [13,14], and others [45,46,51,48,49,56,39,15,52].…”

Section: Clearingmentioning

confidence: 99%

“…Apart from that, we review several other recently proposed niching algorithms, including dynamic fitness sharing (DFS) [12], restricted competition selection (RCS) [29], restricted competition selection with pattern search method (RCS-PSM) [28], the species conserving genetic algorithm (SCGA) [30], the sharing scheme based on niche identification techniques (NIT) [33], a spatiallystructured evolutionary algorithm (SSEA) [13], and the real-coded sequential niching memetic algorithm (SNMA) [53], and compare ENA with them. The commonly used benchmark functions in our test suite allow us to make a direct comparison of the results.…”

Section: Comparison With State-of-the-art Niching Algorithmsmentioning

confidence: 99%

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Ensemble of niching algorithms

Suganthan

2010

Information Sciences

134

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Section: Clearingmentioning

confidence: 99%

Section: Comparison With State-of-the-art Niching Algorithmsmentioning

confidence: 99%

Ensemble of niching algorithms

Suganthan

2010

Information Sciences

134

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“…Related researches are done from the perspective of overcoming shortcomings and enhancing performances of basic methods. A classical niching method requires setting a niche distance threshold [24]. For this problem, a Twin-space Crowding (TC) is introduced to build a parameter-free paradigm to eliminate the effect caused by a parameter value [25].…”

Section: > Replace This Line With Your Paper Identification Number mentioning

confidence: 99%

Multiple-Solution Optimization Strategy for Multirobot Task Allocation

Huang

Ding

Zhou

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-Multiple solutions are often needed because of different kinds of uncertain failures in a plan execution process and scenarios for which precise mathematical models and constraints are difficult to obtain. This work proposes an optimization strategy for multi-robot task allocation (MRTA) problems and makes efforts on offering multiple solutions with same or similar quality for switching and selection. Since the mentioned problem can be regarded as a multimodal optimization one, this work presents a niching immune-based optimization algorithm based on Softmax regression (sNIOA) to handle it. A pre-judgment of population is done before entering an evaluation process to reduce the evaluation time and to avoid unnecessary computation. Furthermore, a guiding mutation operator inspired by the base pair in theory of gene mutation is introduced into sNIOA to strengthen its search ability. When a certain gene mutates, the others in the same gene group are more likely to mutate with a higher probability. Experimental results show the improvement of sNIOA on the aspect of accelerating computation speed with comparison to other heuristic algorithms. They also show the effectiveness of the proposed guiding mutation operator by comparing sNIOA with and without it. Two MRTA application cases are tested finally.Index Terms-Multi-robot task allocation, multimodal optimization, niching immune-based optimization algorithm, Softmax regression, guiding mutation operator.

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“…Therefore, also in this case, the archiving procedure seems to have correctly captured the distribution of the minima, providing information on the structure of the problem. The DM is offered a variety of options which are all admissible, because e is the 11 n/a 8.097E-01 1.088E-01 9.516E-02 x 12 n/a 1.361E-01 4.308E-01 3.963E-01 x 13 n/a 6.566E-01 2.713E-01 4.703E-02 x 14 n/a 4.375E-01 4.908E-01 4.876E-01 x 15 n/a 2.986Eþ00 2.374Eþ00 1.699Eþ00 x 16 n/a 1.050Eþ00 1.050Eþ00 1.050Eþ00 x 17 n/a 3.202Eþ00 3.326Eþ00 3.338Eþ00 x 18 n/a 1.050Eþ00 1.050Eþ00 1.050Eþ00 x 19 rad 3.273Eþ00 3.122Eþ00 3.361Eþ00 x 20 rad À2.187E-01 À4.443E-01 À4.423E-01 x 21 rad 3.135Eþ00 2.556Eþ00 2.560Eþ00 x 22 rad 3.554Eþ00 3.656Eþ00 3.656Eþ00 F(P)…”

Section: The Cassini Casementioning

confidence: 99%

“…Next, there is a certain relation to multi-modal optimization [9][10][11][12][13][14][15][16][17], where the task is to detect all local minima within a given region. However, note that there are some differences to the approach in this study: first, this study is not interested in local minima nor any other point outside E. Second, and that is more important, the present study is not 'restricted' to local minima (though better solutions in a given neighbourhood will be preferred in order to discretize the set of interest E).…”

Section: Introductionmentioning

confidence: 99%

On the detection of nearly optimal solutions in the context of single-objective space mission design problems

Schütze

Lara

Coello

et al. 2011

Proceedings of the Institution of Mechanical Engineers, Part G:

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When making decisions, having multiple options available for a possible realization of the same project can be advantageous. One way to increase the number of interesting choices is to consider, in addition to the optimal solution x*, also nearly optimal or approximate solutions; these alternative solutions differ from x* and can be in different regions -in the design space -but fulfil certain proximity to its function value f(x*). The scope of this article is the efficient computation and discretization of the set E of e-approximate solutions for scalar optimization problems. To accomplish this task, two strategies to archive and update the data of the search procedure will be suggested and investigated. To make emphasis on data storage efficiency, a way to manage significant and insignificant parameters is also presented. Further on, differential evolution will be used together with the new archivers for the computation of E. Finally, the behaviour of the archiver, as well as the efficiency of the resulting search procedure, will be demonstrated on some academic functions as well as on three models related to space mission design.

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A real-coded niching memetic algorithm for continuous multimodal function optimization

Cited by 22 publications

References 12 publications

Ensemble of niching algorithms

Ensemble of niching algorithms

Multiple-Solution Optimization Strategy for Multirobot Task Allocation

On the detection of nearly optimal solutions in the context of single-objective space mission design problems

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