• DocumentCode
    1794679
  • Title

    Common due-window problem: Polynomial algorithms for a given processing sequence

  • Author

    Awasthi, Abhishek ; Lassig, Jorg ; Kramer, Oliver ; Weise, Thomas

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Appl. Sci., Gorlitz, Germany
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    32
  • Lastpage
    39
  • Abstract
    The paper considers the Common Due-Window (CDW) problem where a single machine processes a certain number of jobs against a common due-window. Each job possesses different processing times but different and asymmetric earliness and tardiness penalties. The objective of the problem is to find the processing sequence of jobs, their completion times and the position of the given due-window to minimize the total penalty incurred due to tardiness and earliness of the jobs. This work presents exact polynomial algorithms for optimizing a given job sequence for a single machine with the run-time complexity of O(n2), where n is the number of jobs. We also provide an O(n) algorithm for optimizing the CDW with unit processing times. The algorithms take a sequence consisting of all the jobs (Ji, i = 1, 2, ..., n) as input and return the optimal completion times, which offers the minimum possible total penalty for the sequence. Furthermore, we implement our polynomial algorithms in conjunction with Simulated Annealing (SA) to obtain the best processing sequence. We compare our results with that of Biskup and Feldmann for different due-window lengths.
  • Keywords
    computational complexity; minimisation; simulated annealing; single machine scheduling; CDW optimization; CDW problem; O(n) algorithm; O(n2) run-time complexity; SA; common due-window problem; different-asymmetric earliness penalties; different-asymmetric tardiness penalties; due-window lengths; job processing sequence; job processing times; optimal completion times; polynomial algorithms; simulated annealing; single machine process; total penalty minimization; unit processing times; Job shop scheduling; Optimal scheduling; Polynomials; Schedules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Production and Logistics Systems (CIPLS), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CIPLS.2014.7007158
  • Filename
    7007158