A two‐stage many‐objective evolutionary algorithm with dynamic generalized Pareto dominance
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23016
Abstract: Many‐objective evolutionary algorithms (MaOEAs) are widely used to solve many‐objective optimization problems. As the number of objectives increases, it is difficult to achieve a balance between the population diversity and the convergence. Additionally, the selection… read more here.
Keywords: many objective; generalized pareto; two stage; dynamic generalized ... See more keywords
Ensemble of many-objective evolutionary algorithms for many-objective problems
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DOI: 10.1007/s00500-015-1955-3
Abstract: The performance of most existing multiobjective evolutionary algorithms deteriorates severely in the face of many-objective problems. Many-objective optimization has been gaining increasing attention, and many new many-objective evolutionary algorithms (MaOEA) have recently been proposed. On… read more here.
Keywords: objective evolutionary; many objective; different maoeas; objective problems ... See more keywords
Objective reduction for many-objective optimization problems using objective subspace extraction
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DOI: 10.1007/s00500-017-2498-6
Abstract: Multi-objective evolutionary algorithms (MOEAs) have shown their effectiveness in exploring a well converged and diversified approximation set for multi-objective optimization problems (MOPs) with 2 and 3 objectives. However, most of them perform poorly when tackling… read more here.
Keywords: many objective; objective optimization; optimization; optimization problems ... See more keywords
Many-objective artificial bee colony algorithm for large-scale software module clustering problem
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DOI: 10.1007/s00500-017-2687-3
Abstract: The meta-heuristic search algorithms have been widely applied to solve the various science and engineering optimization problems. However, the performance of these algorithms is highly sensitive toward the number of objective functions and number of… read more here.
Keywords: bee colony; algorithms; many objective; optimization ... See more keywords
Achievement scalarizing function sorting for strength Pareto evolutionary algorithm in many-objective optimization
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DOI: 10.1007/s00521-020-05398-1
Abstract: Multi-objective evolutionary algorithms (MOEAs) have proven their effectiveness in solving two or three objective problems. However, recent research shows that Pareto-based MOEAs encounter selection difficulties facing many similar non-dominated solutions in dealing with many-objective problems.… read more here.
Keywords: function sorting; scalarizing function; many objective; achievement scalarizing ... See more keywords
Hypothesis derivation and its verification by a wholly automated many-objective evolutionary optimization system
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DOI: 10.1007/s00521-021-05786-1
Abstract: This study has constructed a fully automated multidisciplinary and many-objective evolutionary design optimization system independent of computer environments to evaluate objective functions; the research applied it to a geometric design problem of a flyback booster… read more here.
Keywords: optimization; optimization system; objective evolutionary; many objective ... See more keywords
Analysis of a many-objective optimization approach for identifying microservices from legacy systems
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DOI: 10.1007/s10664-021-10049-7
Abstract: The expensive maintenance of legacy systems leads companies to migrate such systems to modern architectures. Microservice architectural style has become a trend to modernize monolithic legacy systems. A microservice architecture consists of small, autonomous, and… read more here.
Keywords: optimization; many objective; legacy systems; approach ... See more keywords
Many-Objective Virtual Machine Placement
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DOI: 10.1007/s10723-017-9399-x
Abstract: The process of selecting which virtual machines (VMs) should be executed at each physical machine (PM) of a virtualized infrastructure is commonly known as Virtual Machine Placement (VMP). This work presents a general many-objective optimization… read more here.
Keywords: machine; many objective; machine placement; problem ... See more keywords
Many-objective interactive optimization and decision making for distribution network expansion planning
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DOI: 10.1016/j.conengprac.2021.104917
Abstract: Abstract This paper establishes a mixed integer linear programming model with many-objective for distribution network expansion planning (DNEP) problem, in which the distributed generation is considered and the original expressions of three commonly used reliability… read more here.
Keywords: optimization; decision making; optimization decision; distribution ... See more keywords
A many-objective optimization model for construction scheduling
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DOI: 10.1080/01446193.2019.1590615
Abstract: Abstract In recent years, the number of stakeholders of construction projects has significantly increased; this has required the simultaneous achievement of competing objectives, such as reductions in the time, cost, resources, and environmental impact of… read more here.
Keywords: construction; many objective; objective optimization; model ... See more keywords
An Adaptative Reference Vector Based Evolutionary Algorithm for Many-Objective Optimization
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DOI: 10.1109/access.2019.2923422
Abstract: Recent studies have shown difficulties in balancing convergence and diversity for many-objective optimization problems with various types of Pareto fronts. This paper proposes an adaptive reference vector based evolutionary algorithm for many-objective optimization, termed as… read more here.
Keywords: many objective; reference vector; objective optimization;