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A many-objective evolutionary algorithm with adaptive convergence calculation
Since different reference points are crucial for calculating convergence, we design a many-objective evolutionary algorithm with an adaptive...
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Achievement scalarizing function sorting for strength Pareto evolutionary algorithm in many-objective optimization
Multi-objective evolutionary algorithms (MOEAs) have proven their effectiveness in solving two or three objective problems. However, recent research...
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Mind the Gap: Measuring Generalization Performance Across Multiple Objectives
Modern machine learning models are often constructed taking into account multiple objectives, e.g., minimizing inference time while also maximizing...
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Development of multi-objective equilibrium optimizer: application to cancer chemotherapy
Any multi-objective optimization algorithms are usually introduced by develo** a single-objective algorithm. In the current study, a recently...
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Silhouetting the Cost-Time Front: Multi-objective Resource Optimization in Business Processes
The allocation of resources in a business process determines the trade-off between cycle time and resource cost. A higher resource utilization leads...
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Random Point Evolution-Based Heuristic for Resource Efficiency in OCDMA Networks
Several practical engineering problems can be modeled as a multi-objective optimization (MOO) problems. In this paper we propose three new heuristics...
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Finding Knees in Bayesian Multi-objective Optimization
Multi-objective optimization requires many evaluations to identify a sufficiently dense approximation of the Pareto front. Especially for a higher...
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A dynamic multiobjective optimization algorithm based on decision variable relationship
Dynamic multiobjective optimization problems exist in daily life and industrial practice. The objectives of dynamic multiobjective optimization...
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A Two-Stage Algorithm for Integer Multiobjective Simulation Optimization
Multiobjective discrete optimization via simulation (MDOvS) has received considerable attention from both academics and industry due to its wide...
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Optimizing storage assignment, order picking, and their interaction in mezzanine warehouses
In warehouses, order picking is known to be the most labor-intensive and costly task in which the employees account for a large part of the warehouse...
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Surrogate-assisted hyper-parameter search for portfolio optimisation: multi-period considerations
Portfolio management is a multi-period multi-objective optimisation problem subject to various constraints. However, portfolio management is treated...
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Multi-objective Optimal Sizing of an AC/DC Grid Connected Microgrid System
Considering the rising energy needs and the depletion of conventional energy sources, microgrid systems combining wind energy and solar photovoltaic...
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Multi-objective quasi-reflection learning and weight strategy-based moth flame optimization algorithm
For the simultaneous optimization of many conflicting objectives, the capability of optimization algorithms must be increased. In this research, a...
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Hybrid Surrogate Assisted Evolutionary Multiobjective Reinforcement Learning for Continuous Robot Control
Many real world reinforcement learning (RL) problems consist of multiple conflicting objective functions that need to be optimized simultaneously....
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Drone flocking optimization using NSGA-II and principal component analysis
Individual agents in natural systems like flocks of birds or schools of fish display a remarkable ability to coordinate and communicate in local...
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Fair and green hyperparameter optimization via multi-objective and multiple information source Bayesian optimization
It has been recently remarked that focusing only on accuracy in searching for optimal Machine Learning models amplifies biases contained in the data,...
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Actor-critic multi-objective reinforcement learning for non-linear utility functions
We propose a novel multi-objective reinforcement learning algorithm that successfully learns the optimal policy even for non-linear utility...
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Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network
Under the development of computing and network convergence, considering the computing and network resources of multiple providers as a whole in a...
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An improved indicator-based two-archive algorithm for many-objective optimization problems
The large number of objectives in many-objective optimization problems (MaOPs) has posed significant challenges to the performance of multi-objective...
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T2RFIS: type-2 regression-based fuzzy inference system
This article discusses a novel type-2 fuzzy inference system with multiple variables in which no fuzzy rules are explicitly defined. By using a...
