Results 151 to 160 of about 2,235,647 (195)

Evolutionary multiobjective optimization

Proceedings of the 10th annual conference companion on Genetic and evolutionary computation, 2007
Many real-world search and optimization problems are naturally posed as non-linear programming problems having multiple conflicting objectives.Due to lack of suitable solution techniques, such problems are usually artificially converted into a single-objective problem and solved.
Eckart Zitzler, Kalyanmoy Deb
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Evolutionary multiobjective optimization

WIREs Data Mining and Knowledge Discovery, 2011
AbstractThis paper presents a very short introduction to multiobjective evolutionary algorithms, including their basic concepts and their main components. The discussion focuses on algorthmic design and, therefore, the issues discussed include selection mechanisms, diversity maintenance mechanisms, and elitism in a multi‐objective context.
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Multiobjective query optimization

Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, 2001
The optimization of queries in distributed database systems is known to be subject to delicate trade-offs. For example, the Mariposa database system allows users to specify a desired delay-cost tradeoff (that is, to supply a decreasing function u(d), specifying how much the user is willing to pay in order to receive the query results within time d ...
Christos H. Papadimitriou, Mihalis Yannakakis   +1 more
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A novel elitist multiobjective optimization algorithm: Multiobjective extremal optimization

European Journal of Operational Research, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Min-Rong Chen, Yong-Zai Lu
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Multiobjective Optimization of Temporal Processes

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2010
This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data.
Zhe Song, Andrew Kusiak
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Approximation in multiobjective optimization

Journal of Global Optimization, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Multiobjective bilevel optimization

Mathematical Programming, 2008
This paper deals with nonlinear non-convex multi-objective bi-level optimization problems which are discussed using an optimistic approach. The author aims to obtain a good approximation of the feasible set of the upper level function by expressing it as the set of minimal solutions of a multi-objective optimization problem.
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On Benson’s scalarization in multiobjective optimization

Optimization Letters, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Majid Soleimani-Damaneh, Moslem Zamani
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Nonconvex Duality in Multiobjective Optimization

Mathematics of Operations Research, 1977
Nonconvex duality properties for multiobjective optimization problems are obtained by using a characterization of Pareto optima by means of generalized Tchebycheff norms. Bounds for the corresponding duality gap are given, and approximate Pareto multipliers are constructed.
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Visualization in Multiobjective Optimization

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016
Bogdan Filipic, Tea Tusar
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