Search Results - "Tanabe, Ryoji"

A Review of Evolutionary Multimodal Multiobjective Optimization by Tanabe, Ryoji, Ishibuchi, Hisao

“…Multimodal multiobjective optimization aims to find all Pareto optimal solutions, including overlapping solutions in the objective space. Multimodal…”
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An easy-to-use real-world multi-objective optimization problem suite by Tanabe, Ryoji, Ishibuchi, Hisao

“…Although synthetic test problems are widely used for the performance assessment of evolutionary multi-objective optimization algorithms, they are likely to…”
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A Framework to Handle Multimodal Multiobjective Optimization in Decomposition-Based Evolutionary Algorithms by Tanabe, Ryoji, Ishibuchi, Hisao

“…Multimodal multiobjective optimization is to locate (almost) equivalent Pareto optimal solutions as many as possible. While decomposition-based evolutionary…”
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Improving the search performance of SHADE using linear population size reduction by Tanabe, Ryoji, Fukunaga, Alex S.

“…SHADE is an adaptive DE which incorporates success-history based parameter adaptation and one of the state-of-the-art DE algorithms. This paper proposes…”
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Success-history based parameter adaptation for Differential Evolution by Tanabe, Ryoji, Fukunaga, Alex

“…Differential Evolution is a simple, but effective approach for numerical optimization. Since the search efficiency of DE depends significantly on its control…”
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An analysis of control parameters of MOEA/D under two different optimization scenarios by Tanabe, Ryoji, Ishibuchi, Hisao

“…•We present an analysis of control parameters of MOEA/D under two scenarios.•Our findings reveal that suitable parameter values for each scenario are…”
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Evaluating the performance of SHADE on CEC 2013 benchmark problems by Tanabe, Ryoji, Fukunaga, Alex

“…This paper evaluates the performance of Success-History based Adaptive DE (SHADE) on the benchmark set for the CEC2013 Competition on Real-Parameter Single…”
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Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios by Tanabe, Ryoji, Ishibuchi, Hisao, Oyama, Akira

“…Recently, a large number of multi-objective evolutionary algorithms (MOEAs) for many-objective optimization problems have been proposed in the evolutionary…”
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Tuning differential evolution for cheap, medium, and expensive computational budgets by Tanabe, Ryoji, Fukunaga, Alex

“…This paper presents a parameter tuning study of Differential Evolution (DE) algorithms, including both standard DE as well as variants of the state-of-the-art…”
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Benchmarking Feature-Based Algorithm Selection Systems for Black-Box Numerical Optimization by Tanabe, Ryoji

“…Feature-based algorithm selection aims to automatically find the best one from a portfolio of optimization algorithms on an unseen problem based on its…”
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Investigating normalization in preference-based evolutionary multi-objective optimization using a reference point by Tanabe, Ryoji

“…Normalization of objectives plays a crucial role in evolutionary multi-objective optimization (EMO) to handle objective functions with different scales, which…”
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Optimization of oil reservoir models using tuned evolutionary algorithms and adaptive differential evolution by Aranha, Claus, Tanabe, Ryoji, Chassagne, Romain, Fukunaga, Alex

“…In the petroleum industry, accurate oil reservoir models are crucial in the decision making process. One critical step in reservoir modeling is History…”
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Evaluation of a randomized parameter setting strategy for island-model evolutionary algorithms by Tanabe, Ryoji, Fukunaga, Alex

“…This paper presents a large-scale, empirical evaluation of a Random, Heterogeneous Island-Model (RHIM) for evolutionary algorithms (EAs), where the control…”
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An Analysis of Quality Indicators Using Approximated Optimal Distributions in a 3-D Objective Space by Tanabe, Ryoji, Ishibuchi, Hisao

“…Although quality indicators play a crucial role in benchmarking evolutionary multiobjective optimization algorithms, their properties are still unclear. One…”
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Reviewing and Benchmarking Parameter Control Methods in Differential Evolution by Tanabe, Ryoji, Fukunaga, Alex

“…Many differential evolution (DE) algorithms with various parameter control methods (PCMs) have been proposed. However, previous studies usually considered PCMs…”
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Quality Indicators for Preference-Based Evolutionary Multi-Objective Optimization Using a Reference Point: A Review and Analysis by Tanabe, Ryoji, Li, Ke

“…Some quality indicators have been proposed for benchmarking preference-based evolutionary multi-objective optimization algorithms using a reference point…”
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A niching indicator-based multi-modal many-objective optimizer by Tanabe, Ryoji, Ishibuchi, Hisao

“…Multi-modal multi-objective optimization is to locate (almost) equivalent Pareto optimal solutions as many as possible. Some evolutionary algorithms for…”
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Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE by Tanabe, Ryoji, Ishibuchi, Hisao

“…A decomposition-based multi-objective evolutionary algorithm with a differential evolution variation operator (MOEA/D-DE) shows high performance on challenging…”
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Neutral-pH peritoneal dialysis solution improves peritoneal function and decreases matrix metalloproteinase-2 (MMP-2) in patients undergoing continuous ambulatory peritoneal dialysis (CAPD) by Nishina, Makoto, Endoh, Masayuki, Suzuki, Daisuke, Tanabe, Ryoji, Endoh, Haruko, Hirahara, Ichiro, Sakai, Hideto

“…Conventional lactate-buffered peritoneal dialysis (PD) solutions have several bioincompatible characteristics, including acidic pH, lactate buffer, and the…”
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Analysis of Prognostic Predictors in Idiopathic Membranous Nephropathy by Wu, Qiong, Jinde, Kiichiro, Nishina, Makoto, Tanabe, Ryoji, Endoh, Masayuki, Okada, Yoshikazu, Sakai, Hideto, Kurokawa, Kiyoshi

“…We studied clinical and histologic parameters at the time of renal biopsy of 19 patients with idiopathic membranous nephropathy (IMN) to investigate the…”
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