Results 1 to 10 of about 1,756,488 (218)
Improved Lebesgue Indicator-Based Evolutionary Algorithm: Reducing Hypervolume Computations [PDF]
Mathematics, 2021 One of the major limitations of evolutionary algorithms based on the Lebesgue measure for multi-objective optimization is the computational cost required to approximate the Pareto front of a problem.
Saúl Zapotecas-Martínez +2 more
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The Hypervolume Indicator [PDF]
ACM Computing Surveys, 2020 The hypervolume indicator is one of the most used set-quality indicators for the assessment of stochastic multiobjective optimizers, as well as for selection in evolutionary multiobjective optimization algorithms.
Andreia P. Guerreiro +2 more
semanticscholar +5 more sources
A multi-objective hybrid algorithm for optimizing neural network architectures in wildlife conservation: a theoretical framework with practical validation [PDF]
Scientific ReportsWildlife conservation applications demand neural network architectures that simultaneously optimize prediction accuracy, computational efficiency, and model interpretability—a challenge inadequately addressed by existing single-objective methods.
Freeson Kaniwa +2 more
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A Fuzzy-Expert enhanced NSGA-II approach for sustainable agricultural systems [PDF]
Scientific ReportsThis study proposes a Fuzzy-Expert-NSGA-II algorithm, an enhanced NSGA-II approach incorporating fuzzy expert systems, for multi-objective optimization of agricultural planting strategies.
Zhonglin Huang +5 more
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The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity [PDF]
International Conference on Evolutionary Multi-Criterion Optimization, 2022 The problem of approximating the Pareto front of a multiobjective optimization problem can be reformulated as the problem of finding a set that maximizes the hypervolume indicator. This paper establishes the analytical expression of the Hessian matrix of
A. Deutz, M. Emmerich, Hao Wang
semanticscholar +1 more source
A Two-Stage Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization
Mathematics, 2023 Many-objective optimization is a critical research topic in the evolutionary computing community. Many algorithms have been proposed to tackle this problem, with evolutionary algorithms based on the hypervolume being among the most effective ones ...
Chengxin Wen, Hongbin Ma
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The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems
Mathematical and Computational Applications, 2023 Recently, the Hypervolume Newton Method (HVN) has been proposed as a fast and precise indicator-based method for solving unconstrained bi-objective optimization problems with objective functions.
Hao Wang +4 more
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Mathematics, 2023 Traveling Salesman Problems (TSPs) have been a long-lasting interesting challenge to researchers in different areas. The difficulty of such problems scales up further when multiple objectives are considered concurrently.
Jeewaka Perera +4 more
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Applied Sciences, 2021 This paper presents a set covering model based on route representation to solve the green ship routing and scheduling problem (GSRSP) with berth time-window constraints for multiple bulk ports.
Apichit Maneengam +1 more
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Bulk Cargo Multimodal Transportation on Inland Waterways Considering Transport Wastage
IEEE Access, 2023 Transportation wastage is inevitable during transportation. With the emergence of container transportation, the transportation wastage generated by most cargo through container transportation has been greatly reduced. However, for products such as grain,
Qingsong Ai +5 more
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