<scp>FOPS</scp>: A new framework for the optimization with variable number of dimensions

Marek, Martin; Kadlec, Petr; Čapek, Miloslav

doi:10.1002/mmce.22335

Cited by 8 publications

(5 citation statements)

References 36 publications

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“…The results are compared with results obtained for VLMOPSO, VNDGDE3, and SCMOPSO algorithms. All the algorithms except for SCMOPSO are implemented using a standalone MATLAB-based toolbox called Fast Optimization ProcedureS (FOPS) [38] that is available online. FOPS is an in-house code developed and maintained at Brno University of Technology.…”

Section: Resultsmentioning

confidence: 99%

“…If not otherwise stated, the controlling parameters of VNDMOPSO are set as summarized in Table 2. The other algorithms use their default settings as described in [38] and in [30] (for the SCMOPSO). Next, the influence of the VNDMOPSO control parameters is evaluated using the benchmark problems.…”

Section: Resultsmentioning

confidence: 99%

“…It contains the definition of all the benchmark problems used in this study to assess the convergence properties of the VNDMOPSO algorithm. This material cites references [32,38,[42][43][44][45].…”

Section: Supplementary Materialsmentioning

confidence: 99%

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Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Kadlec

2023

Algorithms

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This paper aims to solve the space robot pathfinding problem, formulated as a multi-objective (MO) optimization problem with a variable number of dimensions (VND). This formulation enables the search and comparison of potential solutions with different model complexities within a single optimization run. A novel VND MO algorithm based on the well-known particle swarm optimization (PSO) algorithm is introduced and thoroughly described in this paper. The novel VNDMOPSO algorithm is validated on a set of 21 benchmark problems with different dimensionality settings and compared with two other state-of-the-art VND MO algorithms. Then, it is applied to solve five different instances of the space robot pathfinding problem formulated as a VND MO problem where two objectives are considered: (1) the minimal distance of the selected path, and (2) the minimal energy cost (expressed as the number of turning points). VNDMOPSO shows at least comparable or better convergence on the benchmark problems and significantly better convergence properties on the VND pathfinding problems compared with other VND MO algorithms.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Kadlec

2023

Algorithms

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“…For more details about the principles of PSO, the reader is refered to [24]. The MATLAB implementation of the PSO algorithm in the software package FOPS [29] is used in this study.…”

Section: B Global Optimization Approachmentioning

confidence: 99%

Characterizing Scalar Metasurfaces Using Time-Domain Reflectometry

2022

Self Cite

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Two efficient methodologies for the determination of electromagnetic (EM) constitutive properties of scalar metasurfaces are introduced and discussed. In contrast to the available methods, and in line with the recent increasing interest in time-domain (TD) analyses of metasurfaces, we show that the material parameters of a scalar metasurface can be readily achieved directly in the TD merely from the EM reflected pulse shape. The two methodologies are based on an analytical TD reflectometry (TDR) approach and a modern stochastic optimization technique. A number of illustrative numerical examples demonstrating the validity and properties of the proposed techniques are presented.INDEX TERMS electromagnetic transient scattering, inverse scattering problem, metasurface , time-domain analysis.

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“…The benchmark 2 (see Equation ( 21)) is an adaptation of the modified Rastrigin benchmark [51][52][53][54]. Figure 4 show the global and local Pareto set H of benchmark 2.…”

Section: Benchmarkmentioning

confidence: 99%

A Comparison of Archiving Strategies for Characterization of Nearly Optimal Solutions under Multi-Objective Optimization

et al. 2021

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In a multi-objective optimization problem, in addition to optimal solutions, multimodal and/or nearly optimal alternatives can also provide additional useful information for the decision maker. However, obtaining all nearly optimal solutions entails an excessive number of alternatives. Therefore, to consider the nearly optimal solutions, it is convenient to obtain a reduced set, putting the focus on the potentially useful alternatives. These solutions are the alternatives that are close to the optimal solutions in objective space, but which differ significantly in the decision space. To characterize this set, it is essential to simultaneously analyze the decision and objective spaces. One of the crucial points in an evolutionary multi-objective optimization algorithm is the archiving strategy. This is in charge of keeping the solution set, called the archive, updated during the optimization process. The motivation of this work is to analyze the three existing archiving strategies proposed in the literature (ArchiveUpdatePQ,ϵDxy, Archive_nevMOGA, and targetSelect) that aim to characterize the potentially useful solutions. The archivers are evaluated on two benchmarks and in a real engineering example. The contribution clearly shows the main differences between the three archivers. This analysis is useful for the design of evolutionary algorithms that consider nearly optimal solutions.

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FOPS: A new framework for the optimization with variable number of dimensions

Cited by 8 publications

References 36 publications

Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Characterizing Scalar Metasurfaces Using Time-Domain Reflectometry

A Comparison of Archiving Strategies for Characterization of Nearly Optimal Solutions under Multi-Objective Optimization

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