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Dynamic Selection Preference-Assisted Constrained Multiobjective Differential Evolution
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021Solving constrained multiobjective optimization problems brings great challenges to an evolutionary algorithm, since it simultaneously requires the optimization among several conflicting objective functions and the satisfaction of various constraints ...
Kunjie Yu +4 more
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Multiobjective Differential Evolution for Feature Selection in Classification
IEEE Transactions on Cybernetics, 2021Feature selection aims to reduce the number of features and improve the classification accuracy, which is an essential step in many real-world problems.
Peng Wang +3 more
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An Improved Quantum-Inspired Differential Evolution Algorithm for Deep Belief Network
IEEE Transactions on Instrumentation and Measurement, 2020Deep belief network (DBN) is one of the most representative deep learning models. However, it has a disadvantage that the network structure and parameters are basically determined by experiences. In this article, an improved quantum-inspired differential
Wu Deng +4 more
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Improved Multi-operator Differential Evolution Algorithm for Solving Unconstrained Problems
IEEE Congress on Evolutionary Computation, 2020In recent years, several multi-method and multi-operator-based algorithms have been proposed for solving optimization problems. Generally, their performance is better than other algorithms that based on a single operator and/or algorithm.
Karam M. Sallam +3 more
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Is Algebraic Differential Evolution Really a Differential Evolution Scheme?
2021 IEEE Congress on Evolutionary Computation (CEC), 2021The Algebraic Differential Evolution (ADE) is a recently proposed combinatorial evolutionary scheme which mimics the behaviour of the classical Differential Evolution (DE) in discrete search spaces which can be represented as finitely generated groups. ADE has been successfully applied to both permutation and binary optimization problems.
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Comparing black-box differential evolution and classic differential evolution
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018Recently, black-box differential evolution (BBDE) has been proposed to overcome the search biases and sensitivity to rotation of the classic differential evolution (DE). To date, BBDE has been studied only for the 'rand' strategy and even for this strategy, no systematic experimental study has been published yet.
Aljoša Vodopija +2 more
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Differential Evolution: A survey of theoretical analyses
Swarm and Evolutionary Computation, 2019Differential Evolution (DE) is a state-of-the art global optimization technique. Considerable research effort has been made to improve this algorithm and apply it to a variety of practical problems.
K. Opara, J. Arabas
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IEEE Transactions on Cybernetics, 2020
In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously.
Zhengping Liang +4 more
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In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously.
Zhengping Liang +4 more
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Multiobjective Differential Evolution and Differential Evolution for Irrigation Planning
World Environmental and Water Resources Congress 2009, 2009The present paper discusses the applicability of Multiobjective Differential Evolution (MODE) and single objective Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analyzed in the multiobjective framework using MODE.
Piyush Gupta +2 more
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Asynchronous Differential Evolution
IEEE Congress on Evolutionary Computation, 2010This paper introduces the Asynchronous Differential Evolution (ADE) scheme which generalizes the classical Differential Evolution (DE) approach along the dimension of Synchronization Degree (SD). SD regulates the synchrony of the evolution of the current population, i.e. how fast it is replaced by the newly generated population.
Alfredo Milani, Valentino Santucci
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