Abstract The Parallel Machine Scheduling Problem (PMSP) has undergone significant
development in academic literature. The most recent comprehensive review of published …

This paper considers an energy-efficient bi-objective unrelated parallel machine scheduling
problem to minimize both makespan and total energy consumption. The parallel machines …

Bipartite-matching markets pair agents on one side of a market with agents, items, or
contracts on the opposing side. Prior work addresses online bipartite-matching markets …

In classical deterministic scheduling models, it is common to assume that each of the
parameters has only a single predefined value. However, in many applications this is not the …

Recent research on distributionally robust (DR) machine scheduling has used a variety of
approaches to describe the region of ambiguity of uncertain processing times by imposing …

Stochastic scheduling has received much attention from both industry and academia.
Existing works usually focus on random job processing times. However, the uncertainty …

The field of stochastic scheduling is concerned with system models where a set of limited
service resources (eg, servers) must be dynamically allocated over time to jobs with …

This paper establishes performance guarantees for online algorithms that schedule
stochastic, nonpreemptive jobs on unrelated machines to minimize the expected total …

In the analysis of complex stochastic dynamic programs, we often seek strong theoretical
guarantees on the suboptimality of heuristic policies. One technique for obtaining …

This paper investigates a parallel machine scheduling and due date assignment problem
with uncertain job processing times (JPTs) under the earliness and tardiness criteria. To …