首页> 外文会议>AAAI Conference on Artificial Intelligence(AAAI-07); Innovative Applications of Artificial Intelligence Conference(IAAI-07); 20070722-26; 20070722-26; Vancouver(CA); Vancouver(CA) >Towards an Adaptive Approach for Distributed Resource Allocation in a Multi-agent System for Solving Dynamic Vehicle Routing Problems
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Towards an Adaptive Approach for Distributed Resource Allocation in a Multi-agent System for Solving Dynamic Vehicle Routing Problems

机译:在多智能体系统中解决动态车辆路径问题的分布式资源分配自适应方法

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摘要

The existing problem of continuous planning in transportation logistics requires the solving of dynamic Vehicle Routing Problems (dynamic VRPs) which is an NP-complete optimization problem. The task of continuous planning assumes the existence of individual commit times for orders to be released for execution with specific commitment strategies and is similar to the problem of maintaining a guaranteed response time in real-time systems that, in a dynamic environment, applies additional restrictions on planning algorithms. This paper describes the developed multi-agent platform for solving the dynamic multi-vehicle pickup and delivery problem with soft time windows (dynamic m-PDPSTW) that supports goal-driven behavior of autonomous agents with a multi-objective decision-making model. Further research on the design of adaptive mechanisms for run-time feedback-directed adjustment of scheduling algorithms through learning and experience of applied decision options is outlined.
机译:运输物流中连续计划的现有问题需要解决动态车辆路径问题(动态VRP),这是一个NP完全优化问题。连续计划的任务假设要针对要下达的订单使用特定的承诺策略执行的订单存在单独的承诺时间,并且类似于在动态环境中施加额外限制的实时系统中保证响应时间的问题关于规划算法。本文介绍了开发的多智能体平台,该平台可解决带有软时间窗口的动态多车辆收货和交付问题(动态m-PDPSTW),该平台通过多目标决策模型支持自主智能体的目标驱动行为。通过对应用决策选项的学习和经验,概述了对运行时反馈指导的调度算法调整的自适应机制设计的进一步研究。

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