两相随机环境中的队列均衡加入策略
Equilibrium Joining Strategies for Queues in Two-Phase Random Environment
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中文总结 AI 辅助
本文研究两相随机环境下M/M/1排队系统中战略性顾客的均衡加入策略，分析四种观察场景，并在快速振荡和缓慢转换下推导显式解与均衡条件。
中文摘要 AI 辅助
我们研究了一个M/M/1型排队系统中的均衡加入策略，该系统具有战略性顾客，并运行在一个由连续时间马尔可夫过程描述的两相随机环境中。战略性顾客在到达时，根据可用信息和预期效用，权衡服务奖励与等待成本，选择加入或放弃。我们分析了四种观察场景：完全可观察（顾客到达时队列长度和环境相位均被披露）、仅队列可观察、仅环境可观察和完全不可观察。在每种情况下，我们都分析了均衡加入策略。在仅环境可观察和完全不可观察的情况下，我们推导了在环境相位快速振荡和非常缓慢转换下的显式解和均衡条件。
英文摘要
We study equilibrium joining strategies in an M/M/1-type queueing system with strategic customers operating in a two-phase random environment described as a continuous-time Markov process. Strategic customers, upon arrival, choose whether to join or to balk based on available information and anticipated utility, considering the trade-off between reward from service and waiting cost. Four observation scenarios are analysed: fully observable (both queue length and environment phase are disclosed to a customer upon arrival), queue-only observable, environment-only observable, and fully unobservable. In each case, equilibrium joining strategies are analysed. In the environment-only observable and fully unobservable cases, explicit solutions and equilibrium conditions are derived under rapid oscillations and under very slow transitions between environment phases.
发表机构
- Inria Sophia Antipolis, France（法国索菲亚-安蒂波利斯国家信息与自动化研究所）
- Tel Aviv University, Israel（以色列特拉维夫大学）
机构由 AI 辅助整理，请以论文原文为准。
