This paper considers the scheduling of n jobs on m parallel machines to minimize the weighted number of early and tardy jobs. The single machine case of this problem has been shown to be NPcomplete in the strong sense. This problem on m parallel machine is also NP complete in the strong sense and finding an optimal solution appears unlikely. The problem is formulated as an integer linear progra...

hub covering location problem, network design,   single machine scheduling, genetic algorithm,   shuffled frog leaping algorithm   hub location problems (hlp) are synthetic optimization problems that appears in telecommunication and transportation networks where nodes send and receive commodities (i.e., data transmissions, passengers transportation, express packages, postal deliveries, etc.) th...

We study the problem of unrelated parallel-machine scheduling with deteriorating maintenance activities. Each machine has at most one maintenance activity, which can be performed at any time throughout the planning horizon. The length of the maintenance activity increases linearly with its starting time. The objective is to minimize the total completion time or the total machine load. We show t...

We consider an on-line scheduling problem, where jobs arrive one by one to be scheduled on two identical parallel processors with preemption. The objective is to minimize the machine completion time vector with respect to the lp norm. We present a best possible deterministic on-line scheduling algorithm along with a matching lower bound.

We study a parallel job scheduling problem in which parallel jobs may be assigned to any number of processors in a parallel computing system. If a job of size p j is assigned to k j processors, its running time is assumed to be p j=k j + k jc, where c is a constant representing communication overhead for each processor. This model explicitly takes into account the increase in overhead arising f...