Distributed Pareto Local Search for Multi-Objective DCOPs
نویسندگان
چکیده
منابع مشابه
Queued Pareto Local Search for Multi-Objective Optimization
Many real-world optimization problems involve balancing multiple objectives. When there is no solution that is best with respect to all objectives, it is often desirable to compute the Pareto front. This paper proposes queued Pareto local search (QPLS), which improves on existing Pareto local search (PLS) methods by maintaining a queue of improvements preventing premature exclusion of dominated...
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We propose a new Pareto Local Search Algorithm for the many-objective combinatorial optimization. Pareto Local Search proved to be a very effective tool in the case of the bi-objective combinatorial optimization and it was used in a number of the state-of-the-art algorithms for problems of this kind. On the other hand, the standard Pareto Local Search algorithm becomes very inefficient for prob...
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Pareto local search (PLS) is an extension of iterative improvement methods for multi-objective combinatorial optimization problems and an important part of several state-of-the-art multi-objective optimizers. PLS stops when all neighbors of the solutions in its solution archive are dominated. If terminated before completion, it may produce a poor approximation to the Pareto front. This paper pr...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2017
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2016agp0006