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A continuous-time search model with job switch and jumps

机译:具有工作切换和跳跃的连续时间搜索模型

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摘要

We study a new search problem in continuous time. In the traditional approach, the basic formulation is to maximize the expected (discounted) return obtained by taking a job, net of search cost incurred until the job is taken. Implicitly assumed in the traditional modeling is that the agent has no job at all during the search period or her decision on a new job is independent of the job situation she is currently engaged in. In contrast, we incorporate the fact that the agent has a job currently and starts searching a new job. Hence we can handle more realistic situation of the search problem. We provide optimal decision rules as to both quitting the current job and taking a new job as well as explicit solutions and proofs of optimality. Further, we extend to a situation where the agent’s current job satisfaction may be affected by sudden downward jumps (e.g., de-motivating events), where we also find an explicit solution; it is rather a rare case that one finds explicit solutions in control problems using a jump diffusion.
机译:我们不断研究新的搜索问题。在传统方法中,基本公式是最大化接受一份工作后获得的预期(折现)收益(扣除直到该工作开始之前的搜索成本)。传统建模中暗含的假设是,代理在搜索期间根本没有工作,或者她对新工作的决定与她目前所从事的工作情况无关。相反,我们纳入了一个事实,即代理具有当前工作,并开始寻找新工作。因此,我们可以处理更现实的搜索问题。我们提供关于退出当前工作和接受新工作的最佳决策规则,以及明确的解决方案和最优性证明。此外,我们扩展到代理人当前的工作满意度可能受到突然的向下跳动(例如,激励事件)影响的情况,在此我们也找到了明确的解决方案;在极少数情况下,人们会使用跳跃扩散在控制问题中找到明确的解决方案。

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