Stochastic multi-period 2e-clrp

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Guest   imen.ben-mohamed@inria.fr

The algorithm of the paper " A Benders approach for the two-echelon stochastic multi-period capacitated location-routing problem"

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Data formats

The complete data files set can be found on: https://www.math.u-bordeaux.fr/~rsadykov/index.html#instances

The data files are partitioned according to the problem parameters configurations as follows: 

5-4/./.-.-(I1, LT, TC, NIT) 

    random2ELRPdata4-5-4-8-15-1000Sample0NewLow-A
    random2ELRPdata4-5-4-8-20-1000Sample0NewLow-A
    random2ELRPdata4-5-4-8-50-1000Sample0NewLow-A
    random2ELRPdata4-5-4-12-15-1000Sample0NewLow-A
    random2ELRPdata4-5-4-12-20-1000Sample0NewLow-A
    random2ELRPdata4-5-4-12-50-1000Sample0NewLow-A
    random2ELRPdata4-5-4-16-15-1000Sample0NewLow-A
    random2ELRPdata4-5-4-16-20-1000Sample0NewLow-A
    random2ELRPdata4-5-4-16-50-1000Sample0NewLow-A
    random2ELRPdata5-5-4-8-15-1000Sample0NewLow-A
    random2ELRPdata5-5-4-8-20-1000Sample0NewLow-A
    random2ELRPdata5-5-4-8-50-1000Sample0NewLow-A
    random2ELRPdata5-5-4-12-15-1000Sample0NewLow-A
    random2ELRPdata5-5-4-12-20-1000Sample0NewLow-A
    random2ELRPdata5-5-4-12-50-1000Sample0NewLow-A
    random2ELRPdata5-5-4-16-15-1000Sample0NewLow-A
    random2ELRPdata5-5-4-16-20-1000Sample0NewLow-A
    random2ELRPdata5-5-4-16-50-1000Sample0NewLow-A
    random2ELRPdata6-5-4-8-15-1000Sample0NewLow-A
    random2ELRPdata6-5-4-8-20-1000Sample0NewLow-A
    random2ELRPdata6-5-4-8-50-1000Sample0NewLow-A
    random2ELRPdata6-5-4-12-15-1000Sample0NewLow-A
    random2ELRPdata6-5-4-12-20-1000Sample0NewLow-A
    random2ELRPdata6-5-4-12-50-1000Sample0NewLow-A
    random2ELRPdata6-5-4-16-15-1000Sample0NewLow-A
    random2ELRPdata6-5-4-16-20-1000Sample0NewLow-A
    random2ELRPdata6-5-4-16-50-1000Sample0NewLow-A

5-4/./.-.-(I2, LT, TC, NIT) 

    random2ELRPdata4-5-4-8-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata4-5-4-8-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata4-5-4-8-50-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata4-5-4-12-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata4-5-4-12-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata4-5-4-12-50-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-8-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-8-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-8-50-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-12-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-12-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata5-5-4-12-50-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-8-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-8-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-8-50-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-12-15-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-12-20-1000Sample0IncreaseNewLowI2-A
    random2ELRPdata6-5-4-12-50-1000Sample0IncreaseNewLowI2-A

5-4/./.-.-(I1, HT, TC, NIT) 

    random2ELRPdata4-5-4-8-15-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-8-20-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-8-50-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-12-15-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-12-20-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-12-50-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-16-15-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-16-20-1000Sample0NewLow-A\_High
    random2ELRPdata4-5-4-16-50-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-8-15-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-8-20-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-8-50-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-12-15-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-12-20-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-12-50-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-16-15-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-16-20-1000Sample0NewLow-A\_High
    random2ELRPdata5-5-4-16-50-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-8-15-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-8-20-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-8-50-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-12-15-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-12-20-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-12-50-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-16-15-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-16-20-1000Sample0NewLow-A\_High
    random2ELRPdata6-5-4-16-50-1000Sample0NewLow-A\_High

5-4/./.-.-(I1, LT, LC, NIT) 

    random2ELRPdata4-5-4-8-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-8-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-8-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-12-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-12-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-12-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-16-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-16-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata4-5-4-16-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-8-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-8-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-8-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-12-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-12-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-12-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-16-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-16-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata5-5-4-16-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-8-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-8-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-8-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-12-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-12-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-12-50-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-16-15-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-16-20-1000Sample0NewLowLargeCap-A
    random2ELRPdata6-5-4-16-50-1000Sample0NewLowLargeCap-A

5-4/./.-.-(I1, LT, TC, NVT) 

    random2ELRPdata4-5-4-8-15-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-8-20-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-8-50-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-12-15-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-12-20-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-12-50-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-16-15-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-16-20-1000Sample0VariableNewLow-A
    random2ELRPdata4-5-4-16-50-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-8-15-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-8-20-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-8-50-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-12-15-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-12-20-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-12-50-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-16-15-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-16-20-1000Sample0VariableNewLow-A
    random2ELRPdata5-5-4-16-50-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-8-15-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-8-20-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-8-50-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-12-15-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-12-20-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-12-50-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-16-15-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-16-20-1000Sample0VariableNewLow-A
    random2ELRPdata6-5-4-16-50-1000Sample0VariableNewLow-A

Usage

Choose a 2ELRP instance file. 
Set the parameters where the first one should match the name of the file uploaded
Click on "Run this job"
The job may take time. You may follow its progress at any time in your account.
The log file "BaPCod.log" is updated during the run.

Parameters

2ELRP instance filename from the list above
--staticCase=(bool, Default= false): It is false for multi-period case and true for the static case
--nbScenarios=(int, Default=5): the number of demand scenarios to be optimized

Examples

random2ELRPdata4-5-4-8-15-1000Sample0NewLow-A --nbScenarios=10 --staticCase=false

random2ELRPdata4-5-4-12-20-1000Sample0NewLow-A --nbScenarios=15 --staticCase=true

Output

"output.out" is the log file including solutions found and statistics.

"finalSolution.out" provides the final solution obtained by the algorithm: 

    Best dual bound 
    Best primal bound 
    Total time  
    A detailed design solution

27/06/2019 : Version 1.0, initial version updated

How to use our REST API :

Think to check your private token in your account first. You can find more detail in our documentation tab.

This app id is : 203

This curl command will create a job, and return your job url, and also the average execution time

files and/or dataset are optionnal, think to remove them if not wanted 
curl -H 'Authorization: Token token=<your_private_token>' -X POST
-F job[webapp_id]=203
-F job[param]=""
-F job[queue]=standard
-F files[0]=@test.txt
-F files[1]=@test2.csv
-F job[file_url]=<my_file_url>
-F job[dataset]=<my_dataset_name> https://allgo.inria.fr/api/v1/jobs

Then, check your job to get the url files with :

curl -H 'Authorization: Token token=<your_private_token>' -X GET https://allgo.inria.fr/api/v1/jobs/<job_id>