We study inventory control for rental operations in a closed-loop supply chain. In such a system (e.g., Netflix), customers create online queues in a service provider’s website to indicate the items that they would like to rent. Leveraging this advance demand information, we propose effective forecast models and formulate a multi-item inventory control problem. We prove that the (L,U) policy is...

Coupled human balancing tasks are investigated based on both pseudoneural controllers characterized by time-delayed feedback with random gain and natural human balancing tasks. It is shown numerically that, compared to single balancing tasks, balancing tasks coupled by mechanical structures exhibit enhanced stability against balancing errors in terms of both amplitude and velocity and also impr...

We consider the direct application of balancing techniques to unstable periodic systems by extending the balancing concepts to arbitrary periodic systems. We extend first the balancing concepts to unstable discrete-time systems by defining the reachability and observability grammians from appropriate right and left coprime factorizations with inner denominators. Further, we extend this new bala...

Natural selection is expected to leave distinctive signatures on patterns of neutral variation that are tightly linked to a site carrying an advantageous mutation. This notion is the basis for molecular population genetics approaches to the analysis of adaptations in the human genome. In principle, this is an attractive prospect; in practice, several complications and challenges make it difficu...

Load balancing middleware is used extensively to improve scalability and overall system throughput in distributed systems. Many load balancing middleware services are simplistic, however, since they are geared only for specific usecases and environments. These limitations make it hard to use the same load balancing service for anything other than the distributed application it was designed for ...

In this paper, we propose a simple heuristic approach for the inventory control problem with stochastic demand and multiplicative random yield. Our heuristic tries to find the best candidate within a class of policies which are referred to in the literature as the linear inflation rule (LIR) policies. Our approach is computationally fast, easy to implement and intuitive to understand. Moreover,...

the task of balancing of assembly lines is well-known in mass production system but this problem is np-hard even for the simple straight line. therefore, utilizing heuristic methods for these problems is totally unquestionable. furthermore, in line with balancing problems, heuristic methods are the foundation of the metaheuristic methods, thus it seems to be necessary to use more efficient heur...