Semi-online scheduling: A survey

In real-life applications, neither all the inputs of an algorithm are available at outset, as in offline framework, nor do they occur one by order, online setup. Semi-online is intermediate theoretically and practically significant framework with additional information on successive to address limitations frameworks. One key motivation for studying semi-online algorithms investigate how can improve performance algorithms. scheduling, jobs received each job must be scheduled irrevocably before availability next job. scheduling a relaxed variant where some Extra Piece Information (EPI) about whole sequence known priori, or algorithmic extensions allowed. The EPI may include more following parameter(s) such maximum processing time, total sum time jobs, arrival based optimum makespan value, range time. design improved competitive m-machine problem has research attention after seminal works Liu et al. (1996) Kellerer (1997). this survey article, we highlight scholarly contributions state-of-the-art results parallel machine models identical, uniformly related, unbounded batch considering preemptive non-preemptive formats optimality criteria makespan, load balancing, cost, Lp-norm early work maximization, completion plus penalty cost. begins brief introduction frameworks presentation standard well-known measure, analysis. Practical preliminary concepts, motivation, taxonomy presented foundation basic understanding area. State-of-the-art achieved deterministic classified special focus novel intuitions development. We discuss analyze impact A classification references specific outlined further investigation. Finally, conclude non-trivial challenges open problems.