Parameterized Multi-Scenario Single-Machine Scheduling Problems

Danny Hermelin, George Manoussakis, Michael Pinedo, Dvir Shabtay, Liron Yedidsion

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We study a class of multi-scenario single-machine scheduling problems. In this class of problems, we are given a set of scenarios with each one having a different realization of job characteristics. We consider these multi-scenario problems where the scheduling criterion can be any one of the following three: The total weighted completion time, the weighted number of tardy jobs, and the weighted number of jobs completed exactly at their due-date. As all the resulting problems are NP-hard, our analysis focuses on whether any one of the problems becomes tractable when some specific natural parameters are of limited size. The analysis includes the following parameters: The number of jobs with scenario-dependent processing times, the number of jobs with scenario-dependent weights, and the number of different due-dates.

Original languageEnglish
Pages (from-to)2644-2667
Number of pages24
Issue number9
StatePublished - 1 Sep 2020


  • Fixed-parameter tractability
  • Multi-scenario scheduling
  • Parameterized complexity
  • Robust job schedule
  • Single machine scheduling

ASJC Scopus subject areas

  • Computer Science (all)
  • Computer Science Applications
  • Applied Mathematics


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