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Scheduling algorithm for autonomous robot cycle counting

Veneman, T.S. Scheduling algorithm for autonomous robot cycle counting. Master's Thesis / Essay, Industrial Engineering and Management.


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Many companies and universities are developing fully automated cycle counting systems, which make use of autonomous robots, because manual cycle counting is labour intensive. A challenge for achieving fully automated robot cycle counting is the scheduling of the robots to maintain a certain level of inventory accuracy. Therefore, in this thesis a generic scheduling algorithm is developed for planning the routes of the autonomous robots for cycle counting, such that a high level of inventory record accuracy is kept. The algorithm is built by approaching the cycle count scanning problem from a Vehicle Routing Problem perspective. Accounting for the battery depletion, the algorithm schedules multiple trips for the robots each day. This was done with the use of an Adaptive Memory Programming and Tabu Search hybrid metaheuristic algorithm. In addition, the algorithm accounts for recharging times, fixed scanning times per product and a heterogeneous fleet of robots. Furthermore, the algorithm was successfully validated in a case study of a company, that is developing a drone cycle counting system. Lastly, it is shown that four cycle counting methods are compatible with the robot cycle counting system: random sample, ABC, locationbased and supervised learning-based cycle counting.

Item Type: Thesis (Master's Thesis / Essay)
Supervisor name: Jayawardhana, B. and Cao, M.
Degree programme: Industrial Engineering and Management
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 18 Apr 2019 10:38
Last Modified: 23 Apr 2019 13:34

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