We consider the minimum-norm load-balancing (MinNormLB) problem, wherein there are n
jobs, each of which needs to be assigned to one of m machines, and we are given the …

We consider a new scheduling problem on parallel identical machines in which the number
of machines is initially not known, but it follows a given probability distribution. Only after all …

We study the classic problem of minimizing the expected total completion time of jobs on m
identical machines in the setting where the sizes of the jobs are stochastic. Specifically, the …

We consider the stochastic scheduling problem of minimizing the expected makespan on $
m $ parallel identical machines. While the (adaptive) list scheduling policy achieves an …

Abstract We consider the Vector Scheduling problem on identical machines: we have m
machines, and a set J of n jobs, where each job j has a processing-time vector. The goal is …

Motivated by growing interest in optimization under uncertainty, we undertake a systematic
study of designing approximation algorithms for a wide class of 1-stage stochastic …