Knowledge-Driven Multi-Objective Evolutionary Scheduling Algorithm for Cloud Workflows
IEEE Access, 2022 Cloud workflow scheduling often encounters two conflicting optimization objectives of makespan and monetary cost, and is a representative multi-objective optimization problem (MOP).
Ya Zhou, Xiaobo Jiao
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A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems [PDF]
, 2013 This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing based strategies and a genetic local search, aiming at a more flexible ...
A. Jaszkiewicz +54 more
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Efficient Elitist Cooperative Evolutionary Algorithm for Multi-Objective Reinforcement Learning
IEEE Access, 2023 Sequential decision-making problems with multiple objectives are known as multi-objective reinforcement learning. In these scenarios, decision-makers require a complete Pareto front that consists of Pareto optimal solutions. Such a front enables decision-
Dan Zhou, Jiqing Du, Sachiyo Arai
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Runtime Analysis of a Simple Multi-Objective Evolutionary Algorithm [PDF]
, 2005 Practical knowledge on the design and application of multi-objective evolutionary algorithms (MOEAs) is available but well-founded theoretical analyses of the runtime are rare.
Giel, Oliver
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Interval-based ranking in noisy evolutionary multiobjective optimization [PDF]
, 2015 As one of the most competitive approaches to multi-objective optimization, evolutionary algorithms have been shown to obtain very good results for many realworld multi-objective problems.
Bielza Lozoya, Maria Concepcion +2 more
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PSA Based Multi Objective Evolutionary Algorithms [PDF]
, 2014 It has generally been acknowledged that both proximity to the Pareto front and a certain diversity along the front, should be targeted when using evolutionary multiobjective optimization. Recently, a new partitioning mechanism, the Part and Select Algorithm (PSA), has been introduced.
Salomon, S. +6 more
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An Adaptive Constrained Multi-Objective Evolutionary Algorithm Based on Co-Evolutionary [PDF]
Jisuanji gongchengThe solution of Constrained Multi-Objective Optimization(CMOP) problems aims to reasonably allocate limited search resources to satisfy constraints and optimize the objective functions.
HAN Meihui, WANG Peng, LI Ruixu, LIU Zhongyao
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Privacy-Preserving Multi-Objective Evolutionary Algorithms [PDF]
, 2010 Existing privacy-preserving evolutionary algorithms are limited to specific problems securing only cost function evaluation. This lack of functionality and security prevents their use for many security sensitive business optimization problems, such as our use case in collaborative supply chain management.
Funke D., Kerschbaum F.
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Aesthetic Design Using Multi-Objective Evolutionary Algorithms [PDF]
, 2011 The use of computational methodologies for the optimization of aesthetic parameters is not frequent mainly due to the fact that these parameters are not quantifiable and are subjective. In this work an interactive methodology based on the use of multi-objective optimization algorithms is proposed.
Gaspar-Cunha, A. +2 more
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Matching Ontologies through Multi-Objective Evolutionary Algorithm with Relevance Matrix
Mathematics, 2022 The ultimate goal of semantic web (SW) is to implement mutual collaborations among ontology-based intelligent systems. To this end, it is necessary to integrate those domain-independent and cross-domain ontologies by finding the correspondences between ...
Hai Zhu, Xingsi Xue, Hongfeng Wang
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