Benchmark Data

Benchmark Data Set: Unrestricted Common Due Date Problem with Controllable Processing Times

  • Problem Description

    The UCDDCP problem consists of scheduling of a certain number of jobs with controllable processing times on a single machine against a common due-date to minimize the overall earliness/tardiness and the compression penalties of the jobs. The objective of the problem is to find the processing sequence of jobs, the optimal reduction in the processing times of the jobs and their completion times. More details of the problem can be found at ‘undefinedUn-restricted Common Due-Date Problem with Controllable Processing Times - Linear Algorithm for a Given Job Sequence (ICEIS 2015).

    The benchmark instances for the Unrestricted Common Due Date Problem with Controllable Processing Times (UCDDCP) are adapted from the benchmark instances for the Common Due Date (CDD) Problem available in the OR-library, provided by Biskup and Feldmann. As explained above UCDDCP consists of two extra parameters than the CDD problem, namely, the ‘Minimum Processing Time’ and its ‘Compression Penalty’ for any job. The instances provided in the OR-library provide the processing times, earliness/tardiness penalties and the due-date. Hence, we append the information about the minimum processing times (mPi) and the cost of controlling the processing times per unit time (γi). We propose

    • Minimum processing time of any job as mPi ≈ DU(0.6 Pi, Pi) and,
    • Compression penalty as γi ≈ DU(1,5).

    In the above expressions DU(a,b) is a discrete uniform random number between a and b, and Pi is the processing time of any job i. The rest of the parameters remain the same as in undefinedOR-library.

    Benchmark Instances can be downloaded from here.

     

    • Note: The same benchmark instances can as well be used for the Restricted case of the problem, where the due-date is a fraction of the sum of the processing times of all the jobs in any schedule.

     

 

 

 

Letzte Änderung:10. November 2016

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