Search Results - "Constrained multi-objective evolutionary algorithms"
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A two-phase framework of locating the reference point for decomposition-based constrained multi-objective evolutionary algorithms
ISSN: 0950-7051, 1872-7409Published: Amsterdam Elsevier B.V 05.03.2022Published in Knowledge-based systems (05.03.2022)“…Reference point is a key component in decomposition-based constrained multi-objective evolutionary algorithms (CMOEAs…”
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Push and pull search for solving constrained multi-objective optimization problems
ISSN: 2210-6502Published: Elsevier B.V 01.02.2019Published in Swarm and evolutionary computation (01.02.2019)“…This paper proposes a push and pull search (PPS) framework for solving constrained multi-objective optimization problems (CMOPs). To be more specific, the…”
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An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions
ISSN: 1432-7643, 1433-7479Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2019Published in Soft computing (Berlin, Germany) (01.12.2019)“…) to solve constrained multi-objective optimization problems (CMOPs). The proposed constrained multi-objective evolutionary algorithm (CMOEA…”
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MOEA/D with angle-based constrained dominance principle for constrained multi-objective optimization problems
ISSN: 1568-4946, 1872-9681Published: Elsevier B.V 01.01.2019Published in Applied soft computing (01.01.2019)“…This paper proposes a novel constraint-handling mechanism, namely the angle-based constrained dominance principle (ACDP), to solve constrained multi-objective…”
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A coevolutionary constrained multi-objective algorithm with a learning constraint boundary
ISSN: 1568-4946, 1872-9681Published: Elsevier B.V 01.11.2023Published in Applied soft computing (01.11.2023)“…When solving constrained multi-objective optimization problems, the balance of convergence, diversity, and feasibility plays a pivotal role. To address this…”
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Push and pull search embedded in an M2M framework for solving constrained multi-objective optimization problems
ISSN: 2210-6502Published: Elsevier B.V 01.05.2020Published in Swarm and evolutionary computation (01.05.2020)“…In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the…”
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A Dual-Population Constrained Multi-Objective Evolutionary Algorithm with Success Incentive Mechanism and its application to uncertain multimodal transportation problems
ISSN: 0952-1976Published: Elsevier Ltd 26.12.2025Published in Engineering applications of artificial intelligence (26.12.2025)“… To solve this complex problem, this paper introduces a new algorithmic framework. The proposed algorithm, a Dual-Population Constrained Multi-Objective Evolutionary Algorithm with a Success Incentive Mechanism (DSCMOEA…”
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Competition-based two-stage evolutionary algorithm for constrained multi-objective optimization
ISSN: 0378-4754Published: Elsevier B.V 01.04.2025Published in Mathematics and computers in simulation (01.04.2025)“…In recent years, the emergence of constrained multi-objective evolutionary algorithms (CMOEAs…”
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A Pareto front estimation-based constrained multi-objective evolutionary algorithm
ISSN: 0924-669X, 1573-7497Published: New York Springer US 01.05.2023Published in Applied intelligence (Dordrecht, Netherlands) (01.05.2023)“…The balance of convergence, diversity, and feasibility plays a pivotal role in constrained multi-objective optimization problems. To address this issue, in…”
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A Review of Constrained Multi-Objective Evolutionary Algorithm-Based Unmanned Aerial Vehicle Mission Planning: Key Techniques and Challenges
ISSN: 2504-446X, 2504-446XPublished: Basel MDPI AG 01.07.2024Published in Drones (Basel) (01.07.2024)“… struggle to effectively address these difficulties. Constrained multi-objective evolutionary algorithms have been proven to be effective methods for solving complex…”
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A coevolution algorithm based on two-staged strategy for constrained multi-objective problems
ISSN: 0924-669X, 1573-7497Published: New York Springer US 01.12.2022Published in Applied intelligence (Dordrecht, Netherlands) (01.12.2022)“…Constrained Multiobjective Problem (CMOP) is widely used in engineering applications, but the current constrained Multiobjective Optimization algorithms…”
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A comparative study of constrained multi-objective evolutionary algorithms on constrained multi-objective optimization problems
Published: IEEE 01.06.2017Published in 2017 IEEE Congress on Evolutionary Computation (CEC) (01.06.2017)“… This paper first reviews a number of popular constrained multi-objective evolutionary algorithms (CMOEAs…”
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Conference Proceeding -
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A Manipulator Design Optimization Based on Constrained Multi-objective Evolutionary Algorithms
Published: IEEE 01.12.2016Published in 2016 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII) (01.12.2016)“… Finally, constrained multi-objective evolutionary algorithms (CMOEAs) are employed to solve the formulated problem. Several reasonable optimal combinations of geometrical parameters and type selection of motor and gearbox are provided. And compare them with the original structure of UR5…”
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Conference Proceeding -
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A double auxiliary optimization constrained multi-objective evolutionary algorithm
ISSN: 0378-4754, 1872-7166Published: Elsevier B.V 01.06.2024Published in Mathematics and computers in simulation (01.06.2024)“… Motivated by this inspiration, we propose a double auxiliary optimization constrained multi-objective evolutionary algorithm, namely DAO…”
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A constrained multi-objective evolutionary algorithm based on decomposition and dynamic constraint-handling mechanism
ISSN: 1568-4946, 1872-9681Published: Elsevier B.V 01.04.2020Published in Applied soft computing (01.04.2020)“… Some constrained multi-objective evolutionary algorithms (CMOEAs) have been developed for CMOPs, but they still suffer from the problems of easily getting trapped into local optimal solutions and low convergence…”
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A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm
ISSN: 2471-285X, 2471-285XPublished: Piscataway IEEE 01.08.2023Published in IEEE transactions on emerging topics in computational intelligence (01.08.2023)“… Most constrained multi-objective evolutionary algorithms (CMOEAs) are prone to fall into the local optima due to the imbalance between objectives and constraints as well as the poor search ability of the population…”
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A constrained multi-objective evolutionary algorithm with Pareto estimation via neural network
ISSN: 0957-4174, 1873-6793Published: Elsevier Ltd 01.03.2024Published in Expert systems with applications (01.03.2024)“…) lies in achieving a balance among convergence, diversity, and feasibility. To address this issue, this paper proposes a constrained multi-objective evolutionary algorithm with Pareto estimation via neural network named CMOEA-PeNN…”
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A dual dynamic constraint boundary based constrained multi-objective evolutionary algorithm for small feasible regions
ISSN: 0957-4174Published: Elsevier Ltd 25.05.2025Published in Expert systems with applications (25.05.2025)“… struggle to balance feasibility, diversity, and convergence within the population. To overcome this challenge, we propose a dual dynamic constraint boundary-based constrained multi-objective evolutionary algorithm, referred to as TPDCB…”
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A constrained multi-objective evolutionary algorithm based on fitness landscape indicator
ISSN: 1568-4946Published: Elsevier B.V 01.11.2024Published in Applied soft computing (01.11.2024)“… Considering the different requirements of different problems on resource allocation of exploration and exploitation, this paper proposes a new constrained multi-objective evolutionary algorithm based…”
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A flexible two-stage constrained multi-objective evolutionary algorithm based on automatic regulation
ISSN: 0020-0255, 1872-6291Published: Elsevier Inc 01.07.2023Published in Information sciences (01.07.2023)“…The core element in solving constrained multi-objective problems (CMOPs) with evolutionary algorithms is simultaneously balancing objective optimization and…”
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