• DocumentCode
    2362354
  • Title

    Job sequencing with quadratic penalties: An A*-based graph search approach

  • Author

    Sen, Anup K. ; Bagchi, Amitava

  • Author_Institution
    Sch. of Ind. Manage., New Jersey Inst. of Technol., Newark, NJ, USA
  • fYear
    1993
  • fDate
    1-5 Mar 1993
  • Firstpage
    190
  • Lastpage
    196
  • Abstract
    The authors tried to establish that A* is much better than traditional branch-and-bound procedures at solving certain types of minimum-penalty job-sequencing problems. Townsend´s algorithm (1976) for minimum-penalty job sequencing on one machine with quadratic penalties was implemented both as tree search and as a graph-based A* formation that uses Townsend´s lower bounds at nodes as heuristic estimates. The graph implementation took much less time to run, and problem instances of much larger size could be solved. The approach seems to be particularly suitable for sequencing and other optimization problems where lower bounds at nodes can be determined without excessive computational effort
  • Keywords
    graph theory; heuristic programming; optimisation; problem solving; search problems; trees (mathematics); A*; branch-and-bound procedures; computational effort; graph-based A* formation; heuristic estimates; minimum-penalty job-sequencing problem; optimization problems; problem solving; quadratic penalties; tree search; Artificial intelligence; Cities and towns; Electronic mail; Explosions; Operations research; Search methods; Technology management; Traveling salesman problems; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence for Applications, 1993. Proceedings., Ninth Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-8186-3840-0
  • Type

    conf

  • DOI
    10.1109/CAIA.1993.366611
  • Filename
    366611