Results 221 to 230 of about 633,451 (264)
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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 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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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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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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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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An improved multi-objective particle swarm optimizer for multi-objective problems
Expert Systems with Applications, 2010This paper proposes an improved multi-objective particle swarm optimizer with proportional distribution and jump improved operation, named PDJI-MOPSO, for dealing with multi-objective problems. PDJI-MOPSO maintains diversity of new found non-dominated solutions via proportional distribution, and combines advantages of wide-ranged exploration and ...
Shang-Jeng Tsai +5 more
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Evolutionary Computation, 2004
In this paper, an orthogonal multi-objective evolutionary algorithm (OMOEA) is proposed for multi-objective optimization problems (MOPs) with constraints. Firstly, these constraints are taken into account when determining Pareto dominance. As a result, a strict partial-ordered relation is obtained, and feasibility is not considered later in the ...
Sanyou Zeng, Lishan Kang, Lixin Ding
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In this paper, an orthogonal multi-objective evolutionary algorithm (OMOEA) is proposed for multi-objective optimization problems (MOPs) with constraints. Firstly, these constraints are taken into account when determining Pareto dominance. As a result, a strict partial-ordered relation is obtained, and feasibility is not considered later in the ...
Sanyou Zeng, Lishan Kang, Lixin Ding
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1989
A sign of maturity is the recognition that one can’t have everything. Compromise and trade-off are almost always unavoidable in real life decision situations, not only when several parties with non-coincident interests are involved but also when one own’s objectives or desires compete with one another for attention or priorities.
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A sign of maturity is the recognition that one can’t have everything. Compromise and trade-off are almost always unavoidable in real life decision situations, not only when several parties with non-coincident interests are involved but also when one own’s objectives or desires compete with one another for attention or priorities.
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Multi-objective branch and bound
European Journal of Operational Research, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Anthony Przybylski, Xavier Gandibleux
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Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
In this paper we propose an extension of the NM-landscape to model multi-objective problems (MOPs). We illustrate the link between the introduced model and previous landscapes used to study MOPs. Empirical results are presented for a variety of configurations of the multi-objective NM-landscapes.
Roberto Santana 0001 +2 more
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In this paper we propose an extension of the NM-landscape to model multi-objective problems (MOPs). We illustrate the link between the introduced model and previous landscapes used to study MOPs. Empirical results are presented for a variety of configurations of the multi-objective NM-landscapes.
Roberto Santana 0001 +2 more
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