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Optimizing inland container shipping through reinforcement learning
Vid Tomljenovic
,
Yasemin Merzifonluoglu
*
,
Giacomo Spigler
*
Corresponding author for this work
Research Group: Operations Research
Econometrics and OR
Research output
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Contribution to journal
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Article
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Scientific
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peer-review
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Keyphrases
Reinforcement Learning
100%
Inland Container Transportation
100%
High Performance
33%
Decision Maker
33%
Delivery Problem
33%
Customer Service
33%
Decision-making Process
33%
Evolving Environment
33%
Customer Demand
33%
Logistics Demand
33%
Logistics Cost
33%
Efficient Delivery
33%
Reinforcement Learning Algorithm
33%
Rapidly Evolving
33%
Delivery Schedule
33%
Performance Heuristics
33%
Heuristic Policy
33%
Computer Science
Reinforcement Learning
100%
Container
100%
Decision-Making
25%
Decision Maker
25%
Learning Approach
25%
Customer Demand
25%
Problem Setting
25%
Numerical Analysis
25%
Social Sciences
Customer
100%
Decision Maker
50%
Decision-Making Process
50%
Numerical Analysis
50%
Psychology
Decision-Making Process
100%