Powerbank Network Instance Files
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset refers to a network of powerbank (batteries) terminals located in the cities of Rio de Janeiro and Niteroi, Brazil. It contains an array of distances in kilometers between 42 points and five demand scenarios created by Monte Carlo simulation method, using real data from the network.The dataset is used in an optmization model, developed as a mixed integer programming model (MIP) that combines strategic network location and sizing decisions (where to install and the capacity of the terminals) with operational decisions (allocation and reallocation of batteries at the terminals)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Optimization Model"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset refers to a network of powerbank (batteries) terminals located in the cities of Rio de Janeiro and Niteroi, Brazil. It contains an array of distances in kilometers between 42 points and five demand scenarios created by Monte Carlo simulation method, using real data from the network.The dataset is used in an optmization model, developed as a mixed integer programming model (MIP) that combines strategic network location and sizing decisions (where to install and the capacity of the terminals) with operational decisions (allocation and reallocation of batteries at the terminals)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset refers to a network of powerbank (batteries) terminals located in the cities of Rio de Janeiro and Niteroi, Brazil. It contains an array of distances in kilometers between 42 points and five demand scenarios created by Monte Carlo simulation method, using real data from the network.The dataset is used in an optmization model, developed as a mixed integer programming model (MIP) that combines strategic network location and sizing decisions (where to install and the capacity of the terminals) with operational decisions (allocation and reallocation of batteries at the terminals)
Optimization Model