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Raik Stolletz

Researcher at University of Mannheim

Publications -  69
Citations -  1385

Raik Stolletz is an academic researcher from University of Mannheim. The author has contributed to research in topics: Queueing theory & Job shop scheduling. The author has an hindex of 20, co-authored 67 publications receiving 1162 citations. Previous affiliations of Raik Stolletz include Leibniz University of Hanover & Clausthal University of Technology.

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Approximation of the non-stationary M(t)/M(t)/c(t)-queue using stationary queueing models: The stationary backlog-carryover approach

TL;DR: This paper proposes a new approach for the time-dependent analysis of stochastic and non-stationary queueing systems that is based on a stationary backlog-carryover (SBC) approximation of theTime-dependent expected utilization, different approximations of the time -dependent expected queue length and the number of customers in the system are discussed.
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Branch-and-price approaches for the Multiperiod Technician Routing and Scheduling Problem

TL;DR: This paper proposes a mixed integer program and a branch-and-price algorithm to solve a technician routing and scheduling problem motivated by the case of an external maintenance provider.
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Performance Analysis of Time-Dependent Queueing Systems: Survey and Classification

TL;DR: Many queueing systems are subject to time-dependent changes in system parameters, such as the arrival rate or number of servers, and cyclic message volumes in computer systems.
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Performance analysis of time-dependent queueing systems: Survey and classification

TL;DR: In this paper, a survey of approaches for the performance analysis of queueing systems with deterministic parameter changes over time is presented. But the authors focus on time-dependent changes in system parameters, such as the arrival rate or the number of servers.
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Operational workforce planning for check-in counters at airports

TL;DR: In this article, a binary linear programming formulation is developed for the fortnightly tour scheduling problem with flexible employee contracts, which is solved for optimality by CPLEX for real-world demand scenarios with different workforce sizes.