Resource-Constrained Scheduling for Maritime Traffic Management
Authors: Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our scheduling approach on synthetic problems and a real 55-day AIS dataset results in significant reduction of the traffic density while incurring minimal delays. |
| Researcher Affiliation | Academia | Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau {lagussurja, akshatkumar, hclau}@smu.edu.sg School of Information Systems Singapore Management University |
| Pseudocode | Yes | Algorithm 1: CB Decomposition for MTM |
| Open Source Code | No | The paper mentions developing a simulator but does not provide any concrete access information (link or explicit statement) to the source code for the described methodology. |
| Open Datasets | No | We use historical 55-day AIS data for Singapore Straits that records the location of each ship within Straits and port waters at every 5 second interval over 55-days. [...] From the records of each day, we perform the following to create scheduling instances. [...] The paper describes the use of historical AIS data but does not explicitly state that this dataset is publicly available or provide access information such as a link or citation for public access. |
| Dataset Splits | No | The paper describes generating synthetic instances and processing real AIS data, but does not explicitly state training, validation, or test dataset splits or specific splitting methodologies needed for reproduction. |
| Hardware Specification | No | The paper states that the approaches were 'implemented using CPLEX 12.7' and 'CP Optimizer 12.7' but does not provide any specific hardware details such as GPU/CPU models, memory, or cloud resources used for the experiments. |
| Software Dependencies | Yes | Using these synthetic instances, we compare the performance of the combinatorial Benders approach (implemented using CPLEX 12.7) against classical Benders decomposition and the baseline CP approach (implemented using CP Optimizer 12.7). |
| Experiment Setup | Yes | The settings for the three sets of instances are as follows. For all instances, the capacity of each edge is uniformly generated between 1-3, and the minimum time to traverse an edge is sampled uniformly from [5sec, 10sec]. The maximum is set to twice the minimum. The release time of each vessel is uniformly generated between 0-20 seconds, and each activity consumes 1 unit of resources. |