Difference between revisions of "Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics"
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| − | |Summary=For a group of robots | + | |Summary=For a group of robots or forklifts involved in warehouses, Sony Mobile in Lund has a Masters Thesis project. The aim is to generate paths/routes for all vehicles according to a pre-determined schedule. This is a NP-hard problem termed as vehicle routing problem and has been solved using heuristic approaches. Here, we try to use Deep Q learning to solve it. |
|Keywords=vehicle routing problem, Reinforcement learning | |Keywords=vehicle routing problem, Reinforcement learning | ||
| − | |Supervisor=Jennifer David, Thorsteinn Rögnvaldsson, | + | |Supervisor=Jennifer David, Thorsteinn Rögnvaldsson, |
|Level=Master | |Level=Master | ||
|Status=Open | |Status=Open | ||
}} | }} | ||
Revision as of 16:57, 19 October 2018
| Title | Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics |
|---|---|
| Summary | String representation "For a group of … ng to solve it." is too long. |
| Keywords | vehicle routing problem, Reinforcement learning |
| TimeFrame | |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | Jennifer David, Thorsteinn Rögnvaldsson |
| Level | Master |
| Status | Open |
