  In online scheduling, jobs are available one by one and each job must be
scheduled irrevocably before the availability of the next job. Semi-online
scheduling is a relaxed variant of online scheduling, where an additional
memory in terms of buffer or an Extra Piece of Information(EPI) is provided
along with input data. The EPI may include one or more of the parameter(s) such
as size of the largest job, total size of all jobs, arrival sequence of the
jobs, optimum makespan value or range of job's processing time. A semi-online
scheduling algorithm was first introduced in 1997 by Kellerer et al. They
envisioned semi-online scheduling as a practically significant model and
obtained improved results for $2$-identical machine setting. This paper surveys
scholarly contributions in the design of semi-online scheduling algorithms in
parallel machine models such as identical and uniformly related by considering
job's processing formats such as preemptive and non-preemptive with the
optimality criteria such as Min-Max and Max-Min. The main focus is to present
state of the art competitive analysis results of well-known semi-online
scheduling algorithms in a chronological overview. The survey first introduces
the online and semi-online algorithmic frameworks for the multi-processor
scheduling problem with important applications and research motivation,
followed by a taxonomy for semi-online scheduling. Fifteen well-known
semi-online scheduling algorithms are stated. Important competitive analysis
results are presented in a chronological way by highlighting the critical ideas
and intuition behind the results. An evolution time-line of semi-online
scheduling setups and a classification of the references based on EPI are
outlined. Finally, the survey concludes with the exploration of some of the
interesting research challenges and open problems.
