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Multi-objective evolution strategy for multimodal multi-objective optimization
Applied Soft Computing, 2021Abstract In the past decades, various effective and efficient multi-objective evolutionary algorithms (MOEAs) have been proposed for solving multi-objective optimization problems. However, existing MOEAs cannot satisfactorily address multimodal multi-objective optimization problems that demand to find multiple groups of optimal solutions ...
Kai Zhang 0002 +3 more
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Multi-Objective Clustering Ensemble
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06), 2006In this paper we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is constituted by a Pareto-based multi-objective genetic algorithm that uses clustering validation measures as the objective functions.
Katti Faceli +2 more
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Progressive Multi-Objective Optimization
International Journal of Information Technology & Decision Making, 2014This paper introduces progressive multi-objective optimization (PMOO), a novel technique to include the decision maker's preferences into the multi-objective optimization process. PMOO integrates a well-known method for multi-criteria decision making (PROMETHEE) into a simple multi-objective metaheuristic by maintaining and updating a small reference ...
Kenneth Sörensen, Johan Springael
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Multi‐objective ensemble generation
WIREs Data Mining and Knowledge Discovery, 2015Ensemble methods that combine a committee of machine‐learning models, each known as a member or base learner, have gained research interests in the past decade. One interest on ensemble generation involves the multi‐objective approach, which attempts to generate both accurate and diverse members that fulfill the theoretical requirements of good ...
Shenkai Gu, Ran Cheng 0004, Yaochu Jin
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Multi-Objective A* Algorithm for the Multimodal Multi-Objective Path Planning Optimization
2021 IEEE Congress on Evolutionary Computation (CEC), 2021In this paper, we consider the multimodal multi-objective path planning (MMOPP) optimization, which is the main topic of a special session in IEEE CEC 2021. The MMOPP aims at finding all the Pareto optimal paths from a start area to a goal area on a grid map, while passing through several designated must-visit areas.
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1997
In the standard ``single-object'''' model of shared-memory computing, it is assumed that a process accesses at most one shared object in each of its steps. In this paper, we consider a more powerful variant---the ``multi-object'''' model---in which each process may access *any* finite number of shared objects atomically in each of its steps. We present
Prasad Jayanti, Sanjay Khanna
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In the standard ``single-object'''' model of shared-memory computing, it is assumed that a process accesses at most one shared object in each of its steps. In this paper, we consider a more powerful variant---the ``multi-object'''' model---in which each process may access *any* finite number of shared objects atomically in each of its steps. We present
Prasad Jayanti, Sanjay Khanna
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Multi-objective diversity maintenance
Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2006Paul Snijders Kunstmatige Intelligentie Groningen University Grote Kruisstraat 2/1 9712 TS Groningen, The Netherlands P.Snijders@ai.rug.nl Edwin D. de Jong Institute of Information and Computing Sciences Utrecht University PO Box 80.089 3508 TB Utrecht, The Netherlands dejong@cs.uu.nl Bart de Boer Kunstmatige Intelligentie Groningen University Grote ...
Snijders, P. +3 more
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Automatic Configuration of Multi-objective Optimizers and Multi-objective Configuration
2019Heuristic optimizers are an important tool in academia and industry, and their performance-optimizing configuration requires a significant amount of expertise. As the proper configuration of algorithms is a crucial aspect in the engineering of heuristic algorithms, a significant research effort has been dedicated over the last years towards moving this
Bezerra, Leonardo C.T. +2 more
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Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
Soft Computing, 2016Multi-objective optimization problems (MOPs) are very common in practice. To solve MOPs, many kinds of multi-objective evolutionary algorithms (MOEAs) are proposed. However, different MOEAs have different performances for different MOPs. Therefore, it is a time-consuming task to choose a suitable MOEA for a given problem.
Weian Guo +3 more
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