A class of on-line scheduling algorithms to minimize total completion time

A class of on-line scheduling algorithms to minimize total completion time

We consider the problem of scheduling jobs on-line on a single machine and on identical machines with the objective to minimize total completion time. We assume that the jobs arrive over time. We give a general 2-competitive algorithm for the single machine problem. The algorithm is based on delaying the release time of the jobs, i.e., making the jobs artificially later available to the on-line...

On-line scheduling to minimize average completion time revisited

We consider the scheduling problem of minimizing the average-weighted completion time on identical parallel machines when jobs are arriving over time. For both the preemptive and the nonpreemptive setting, we show that straightforward extensions of Smith’s ratio rule yield smaller competitive ratios than the previously best-known deterministic on-line algorithms. c © 2003 Elsevier B.V. All righ...

Customer Order Scheduling to Minimize Total Weighted Completion Time

In this paper we study the scheduling problem in which each customer order consists of several jobs of different types, which are to be processed on m facilities. Each facility is dedicated to the processing of only one type of jobs. All jobs of an order have to be delivered to the customer at the same time. The objective is to schedule all the orders to minimize the total weighted order comple...

Scheduling Identical Parallel Machines to Minimize Total Weighted Completion Time

Scheduling with Rejection to Minimize the Total Weighted Completion Time∗

In this paper, we address the scheduling problem with rejection in which we can choose a subset of jobs to process. Choosing not to process any job incurs a corresponding penalty. We consider the following problem for the first time: scheduling with rejection to minimize the total weighted completion time with the constraint of total penalties on identical parallel machines, where the number of...