Improving the anytime behavior of two-phase local search
نویسندگان
چکیده
منابع مشابه
Adaptive "Anytime" Two-Phase Local Search
Two-Phase Local Search (TPLS) is a general algorithmic framework for multi-objective optimization. TPLS transforms the multi-objective problem into a sequence of single-objective ones by means of weighted sum aggregations. This paper studies different sequences of weights for defining the aggregated problems for the bi-objective case. In particular, we propose two weight setting strategies that...
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Anytime local search for distributed constraint optimization
Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small problems. Distributed local search algorithms can be used for solving DisCOPs. However, because of the differences between the global evaluation of a system’s state and the private evaluation of states by agents, agents ar...
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Distributed Constraint Optimization Problems (DCOPs) are an elegant model for representing and solving many realistic combinatorial problems that are distributed by nature. DCOPs are NP-hard and therefore many recent studies consider incomplete algorithms for solving them. Distributed local search algorithms, in which agents in the system hold value assignments to their variables and iterativel...
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Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small problems. Distributed local search algorithms can be used for solving DisCOPs. However, because of the differences between the global evaluation of a system’s state and the private evaluation of states by agents, agents ar...
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ژورنال
عنوان ژورنال: Annals of Mathematics and Artificial Intelligence
سال: 2011
ISSN: 1012-2443,1573-7470
DOI: 10.1007/s10472-011-9235-0