Enabling Sustainable Freight Forwarding Network via Collaborative Games

Authors: Pang-Jin Tan, Shih-Fen Cheng, Richard Chen

IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental In our first experiment, we compare the runtime between FSLCG and the baseline method by Skibski et al. (2014) as we vary the number of forwarders from 5 to 30.
Researcher Affiliation Collaboration Pang-Jin Tan1 , Shih-Fen Cheng1 , Richard Chen2 1Singapore Management University 2Coupang
Pseudocode Yes Algorithm 1 Fast Shapley for LCG (FS-LCG)
Open Source Code No The paper does not provide any links or explicit statements about the availability of open-source code for the described methodology.
Open Datasets No The paper describes parameters used to generate experimental data (e.g., 'The cost of a box is drawn from U(700, 1300)'), but it does not specify a publicly available or open dataset with access information.
Dataset Splits No The paper does not provide specific training/validation/test dataset splits needed to reproduce the experiment.
Hardware Specification No The paper does not explicitly describe the specific hardware used to run its experiments.
Software Dependencies No The paper does not provide a reproducible description of ancillary software with specific version numbers for key components used in its experiments.
Experiment Setup Yes In the first experiment, the objective is to understand the performance of FS-LCG in a general setting. We have 100 port pairs with the number of services per port pair set range between 1 and 5. We then randomly distribute these services uniformly across the forwarders. The cost of a box is drawn from U(700, 1300), the number of boxes for a service is drawn from U(20, 80), the number of transport requests per service is drawn from U(1, 5), and the volume of transport request is drawn from U(1, 29).