Difference between revisions of "Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics"
From ISLAB/CAISR
(Created page with "{{StudentProjectTemplate |Summary=For a group of robots/vehicles/forklifts involved in warehouses, Sony Mobile in Lund has a Masters Thesis project. The aim is to generate pat...") |
|||
Line 1: | Line 1: | ||
{{StudentProjectTemplate | {{StudentProjectTemplate | ||
− | |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 |