D

  • Gurobi-versary
  • Investigator
  • Conversationalist
  • 合計アクティビティ 48
  • 前回のアクティビティ
  • メンバー登録日
  • フォロー 0ユーザー
  • フォロワー 0ユーザー
  • 投票 6
  • サブスクリプション 18

アクティビティの概要

Dさんの最近のアクティビティ
  • Dさんが投稿を作成しました:

    Model is leading to suboptimal results in only some iterations

    ユーザーの入力を待っています。

    I am running my small-version of my model on multiple combination parameters. It's a simple experiments to sanity-check the results of the model. For selected parameter combination the model is cle...

  • Dさんが投稿を作成しました:

    Catastrophic Forgetting

    回答済み

    Does gurobi suffer from catastrophic forgetting?

  • Dさんが投稿を作成しました:

    Could different hardware give different results?

    回答済み

    I am running the same model on two different PCs, and given the same parameters and time limit, one is giving about 0.055% optimality gap, while the other is giving 85% optimality gap and way lower...

  • Dさんがコメントを作成しました:

    over 3 hours

  • Dさんがコメントを作成しました:

    Yes, I am using jupyter notebook.  The problem is that it is stuck and it doesn't give any further messages after  Continuing optimization...

  • Dさんが投稿を作成しました:

    Issue with Scaling the model

    回答済み

    What could be the issue and how can I solve it, when I am having successful matches (solutions) for a small number of input dataset, however when I input a larger dataset that includes the smaller ...

  • Dさんがコメントを作成しました:

    What does parameter Heuristics do?  Also, can I write any model as .mps too?  And thanks for answering my original question. 

  • Dさんが投稿を作成しました:

    Presolve

    回答済み

    What does Presolve exactly do?

  • Dさんが投稿を作成しました:

    Continuing optimization...

    回答済み

    What does it mean when I see this in the log for a while "Continuing optimization... ", even though I used the parameter: model.Params.OutputFlag = 1, to get detailed information during the optimzi...

  • Dさんが投稿を作成しました:

    Running consecutive optimizations on the same model

    進行中

    What exactly happens when I construct a model, run an optimization, then change the parameters, and run the optimization again? Does the second run learn from the first run and start where it left ...