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Multi-objective Optimization for the Design of Salary Structures
In a context of labor shortage and strong global competition for talent, salary management is becoming a critical issue for companies wishing to...
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AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification
Automated Machine Learning (AutoML) has achieved high popularity in recent years. However, most of these studies have investigated alternatives to...
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A tri-stage competitive swarm optimizer for constrained multi-objective optimization
Objective optimization and constraint satisfaction should be considered simultaneously when dealing with constrained multi-objective optimization...
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Solving Constrained Multi-objective Optimization Problems with Passive Archiving Mechanism
During these years, many advanced constrained multi-objective evolutionary algorithms (CMOEAs) have been developed to solve constrained...
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An Extension of a Dynamic Heuristic Solution for Solving a Multi-Objective Optimization Problem in the Defense Industry
Project scheduling in a real-life scenario often involves multiple-criteria decision-making in which no single solution exists. To solve such a...
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Conditional probability table limit-based quantization for Bayesian networks: model quality, data fidelity and structure score
Bayesian Networks (BN) are robust probabilistic graphical models mainly used with discrete random variables requiring discretization and quantization...
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Reference point reconstruction-based firefly algorithm for irregular multi-objective optimization
Reference point-based environmental selection has achieved promising performance in multi-objective optimization problems. However, when solving the...
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A Game Theoretic Perspective on Bayesian Many-Objective Optimization
This chapter addresses the question of how to efficiently solve many-objective optimization problems in a computationally demanding black-box...
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A First Runtime Analysis of the NSGA-II on a Multimodal Problem
Very recently, the first mathematical runtime analyses of the multi-objective evolutionary optimizer NSGA-II have been conducted. We continue this...
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An Improved Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization
The hypervolume indicator is commonly utilized in indicator-based evolutionary algorithms due to its strict adherence to the Pareto domination...
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Three-Phase Hybrid Evolutionary Algorithm for the Bi-Objective Travelling Salesman Problem
In this research paper, we address the Bi-objective Traveling Salesman Problem (BTSP), which involves minimizing two conflicting objectives: travel...
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A multi-population evolutionary algorithm for multi-objective constrained portfolio optimization problem
Due to the rapid development of the financial market, the portfolio selection problem has become of the most complex problem in finance. This paper...
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Multi-objective evolutionary algorithm on reliability redundancy allocation with interval alternatives for system parameters
This paper presents a multi-objective reliability redundancy allocation model with constraints representing the system complexity. A reliability...
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A SHADE-based multimodal multi-objective evolutionary algorithm with fitness sharing
In the multimodal multi-objective optimization problems (MMOPs), at least two equivalent Pareto optimal solutions in decision space with an identical...
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A large-scale multiobjective evolutionary algorithm with overlap** decomposition and adaptive reference point selection
Many large-scale multiobjective optimization problems with large decision space hinder the convergence search of evolutionary algorithms in various...
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Search-Based Optimisation of LLM Learning Shots for Story Point Estimation
One of the ways Large Language Models (LLMs) are used to perform machine learning tasks is to provide them with a few examples before asking them to...
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Take a Close Look at the Optimization of Deep Kernels for Non-parametric Two-Sample Tests
The maximum mean discrepancy (MMD) test with deep kernel is a powerful method to distinguish whether two samples are drawn from the same...
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Multiobjective energy efficient street lighting framework: A data analysis approach
A data analysis approach for designing an energy efficient street lighting framework is proposed to maximize both energy efficiency and uniformity of...
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An external archive guided Harris Hawks optimization using strengthened dominance relation for multi-objective optimization problems
In this paper, Multi-Objective Harris Hawks Optimization (MOHHO) is proposed based on strengthened dominance relation (SRD) to solve multi-objective...
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Multi-objective path planning for lung biopsy surgery
CT image-guided lung biopsy surgery is the gold standard for lung tumor diagnosis. The preoperative path planning of the surgery is necessary, which...
