An online non-convex optimization problem is considered where the goal is to minimize the flow time (total delay) of a set of jobs by modulating the number of active servers, but with a switching cost associated with changing the number of active servers over time. Each job can be processed by at most one fixed speed server at any time. Compared to the usual online convex optimization (OCO) problem with switching cost, the objective function considered is non-convex and more importantly, at each time, it depends on all past decisions and not just the present one. Both worst-case and stochastic inputs are considered; for both cases, competitive algorithms are derived.

中文翻译：

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容量配置引发的内存和切换成本在线非凸优化问题

考虑在线非凸优化问题，其目标是通过调节活动服务器的数量来最小化一组作业的流动时间（总延迟），但会产生与随时间变化的活动服务器数量相关的切换成本。每个作业在任何时间最多可以由一台定速服务器处理。与通常的具有切换成本的在线凸优化（OCO）问题相比，所考虑的目标函数是非凸的，更重要的是，在每一时刻，它都取决于所有过去的决策而不仅仅是当前的决策。最坏情况和随机输入都被考虑；对于这两种情况，都得出了竞争算法。