首页> 外文会议>Proceedings of the Third IASTED International Conference on Advances in Computer Science and Technology >A SEARCH METHOD FOR REDUCING LOCAL COST IN DISTRIBUTED CONSTRAINT OPTIMIZATION PROBLEM
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A SEARCH METHOD FOR REDUCING LOCAL COST IN DISTRIBUTED CONSTRAINT OPTIMIZATION PROBLEM

机译:降低分布式约束优化问题中本地成本的搜索方法

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摘要

A distributed constraint optimization problem (DCOP) distributes the variables and constraints among intelligent agents to enable it to be treated as a constraint satisfaction problem. In this paper, we propose a search method based on the asynchronous distributed optimization (Adopt) algorithm that has been proposed for DCOP. Adopt is a complete method based on a depth-first-search, and operates asynchronously to find the optimal solution for the overall cost. We propose a distributed search method that builds on the merits of Adopt by considering the local load of each agent as opposed to overall optimization. The effect of the proposal was evaluated in simulations.
机译:分布式约束优化问题(DCOP)在智能代理之间分配变量和约束,以使其能够被视为约束满足问题。在本文中,我们提出了一种针对DCOP提出的基于异步分布式优化(Adopt)算法的搜索方法。采用是基于深度优先搜索的完整方法,并且异步操作以找到总成本的最佳解决方案。我们提出一种分布式搜索方法,该方法基于Adopt的优点,通过考虑每个代理的本地负载而不是整体优化来实现。在模拟中评估了该建议的效果。

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