we consider online scheduling of jobs with specic release time on m identical machines. each job has a weight and a size; the goal is maximizing total weight of completed jobs. at release time of a job it must immediately be scheduled on a machine or it will be rejected. it is also allowed during execution of a job to preempt it; however, it will be lost and only weight of completed jobs contr...

We consider online scheduling of jobs with specic release time on m identical machines. Each job has a weight and a size; the goal is maximizing total weight of completed jobs. At release time of a job it must immediately be scheduled on a machine or it will be rejected. It is also allowed during execution of a job to preempt it; however, it will be lost and only weight of completed jobs contri...

This paper presents a novel, integer-linear programming (ILP) model for an identical parallel-machine scheduling problem with family setup times that minimizes the total weighted flow time (TWFT). Some researchers have addressed parallel-machine scheduling problems in the literature over the last three decades. However, the existing studies have been limited to the research of independent jobs,...

We consider the stochastic identical parallel machine scheduling problem and its online extension, when the objective is to minimize the expected total weighted completion time of a set of jobs that are released over time. We give randomized as well as deterministic online and offline algorithms that have the best known performance guarantees in either setting, online or offline and determinist...

With the increasing popularity of large-scale distributed computing networks, a new aspect has to be considered for scheduling problems: machines may not be available permanently, but may be withdrawn and reappear later. We give several results for completion time based objectives: 1. we show that scheduling independent jobs on identical machines with online failures to minimize the sum of comp...

We consider the problem of scheduling periodic task sets on identical multiprocessors. In this case deadlines are equal periods, although results described here can be applied to sporadic task sets with periods not equal to deadlines. We present an online scheduling policy that can be used to design scheduling algorithms. We came up with scheduling rules to minimize the number of preemptions an...

We study classic machine sequencing problems in an online setting. Specifically, we look at deterministic and randomized algorithms for the problem of scheduling jobs with release dates on identical parallel machines, to minimize the sum of weighted completion times: Both preemptive and non-preemptive versions are analyzed. Using linear programming techniques, borrowed from the single machine c...

This thesis presents new and improved scheduling algorithms for a number of scheduling problems. The first part of the thesis deals with two online-list scheduling problems, both with the objective to minimize the makespan. In these problems, the jobs arrive one by one and the decision maker has to irrevocably schedule the arriving job before the next job becomes known. In the second part, a ne...

We provide a general scheme for constructing monotone algorithms for a wide class C of scheduling problems Q|prec, rj |γ on related machines with precedence constraints and/or release dates. Our scheme works in the offline and the online setting. It takes as input two approximation/competitive algorithms for the (simpler) scheduling problems P |prec, rj |γ on identical machines and 1|prec, rj |...