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As quantum computation grows, the number of qubits involved in a given quantum computer increases. But due to the physical limitations in the number of qubits of a single quantum device, the computation should be performed in a distributed system. ...

Dominance resistance is a challenge for Pareto-based multi-objective evolutionary algorithms to solve the high-dimensional optimization problems. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) still has such disadvantage even though it ...

As most of Multi-Objective Evolutionary Algorithms (MOEAs) scale quite poorly when the number of objective functions increases, new strategies have been proposed to face this limitation. Considered one of the most well-succeeded examples of such ...

Jamming Grippers are a novel class of soft robotic actuators that can robustly grasp and manipulate objects of arbitrary shape. They are formed by placing a granular material within a flexible skin connected to a vacuum pump and function by pressing the ...

Under the background of the new medical reform, the pharmaceutical industry is in constant transformation and upgrading, and the establishment of a rational and efficient pharmaceutical logistics system is imminent. Carbon emission, cost and time are set ...

Neural networks are arising a wave in the various areas of artificial intelligence and they have adopted in daily life successfully. The structure tuning of neural networks is crucial when building the relative models. The structure of neural networks is ...

Considering the various uncertainties in the implementation process of high-end equipment development tasks, the Monte Carlo simulation method is used to simulate the execution process of these tasks. Parameters such as the average duration and ...

Most optimization-based community detection approaches formulate the problem in a single- or bi-objective framework. In this paper, we propose two variants of a three-objective function optimization formulation using a customized non-dominated ...

Since the findings of the single modality data are unable to provide sufficient sensitivity and specificity for diagnostic measures, multimodality data fusion is adopted in the neuroimaging to detect the important differences between patients and ...

Intrusion detection systems (IDSs) is crucial for the security of Vehicle Ad Hoc Networks (VANETs), as it can accurately detect both the inner and outer attacks. However, the redundant features and the sparse samples of fatal attacks in VANETs datasets ...

Dominance resistant solutions (DRSs) in multi-objective problems have very good values for some objectives and very bad values for other objectives. Whereas DRSs are far away from the Pareto front, they are hardly dominated by other solutions due to ...

Sustainable forest management is a crucial element in combating climate change, plastic pollution, and other unsolved challenges of the 21st century. Forests not only produce wood - a renewable resource that is increasingly replacing fossil-based ...

Recently, more and more multi/many-objective algorithms have been proposed. However, most evolutionary algorithms only focus on solving small-scale multi/many-objective optimization problems, and few researchers pay attention to solving large-...

• Information feedback models are to improve NSGA-III to solve large-scale problems.
• Individuals’ historical information was reused via the information feedback model.
• Individuals’ historical information is selected with a fixed way ...

• A novel model is proposed for the PM2.5 concentrations multi-step prediction.
• ...

PM2.5 concentrations forecasting can provide early air pollution warning information for the public in advance. In this study, a novel multi-resolution ensemble model for multi-step PM2.5 concentrations forecasting is proposed. This ...

This paper proposes a novel master–slave parallel evolutionary algorithm (EA) approach with different asynchrony and provides its detailed analyses on multi-objective optimization problems. We express the proposed EA with different asynchrony as a ...

• The performance of three crossover operators of NSGA-III algorithm on big data optimization problems are investigated.
• By introducing the concept of Stud, several improved crossover operators of SBX, UC, and SI have been designed.
• ...

Traditional multi-objective optimization evolutionary algorithms (MOEAs) do not usually meet the requirements for online data processing because of their high computational costs. This drawback has resulted in difficulties in the deployment of ...

• A modified NSGA-III algorithm is proposed for sensor placement.
• We ...

Contaminant events in drinkable water distribution systems (WDSs) have occurred frequently in recent years, causing severe damages, economic loss, and long-lasting societal impact. A critical and effective method to monitor WDS in real-...

• The problem of multi-objective project portfolio optimization with interval uncertainties is addressed.

In this paper, multi-objective project portfolio optimization problem, with interval uncertainties, is addressed. Due to the existence of internal and external uncertainties, the robust optimization approach is selected. We have ...

Many-objective optimization problems abbreviated as MaOPs with more than three objectives have attracted increasing interests due to their widely existing in a variety of real-world applications. This paper presents a novel many-...

To support semantic inter‐operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts ...