This survey covers the basic principles and related works addressing the time-triggered
scheduling of periodic tasks with deadlines. The wide range of applications and the …

In this paper we analyze a parallel machine scheduling problem in which the processing of
jobs on the machines requires a number of units of a scarce resource. This number depends …

Combinatorial optimization (CO) layers in machine learning (ML) pipelines are a powerful
tool to tackle data-driven decision tasks, but they come with two main challenges. First, the …

In this paper, we study the unrelated parallel machine scheduling problem with one scarce
additional resource to minimise the maximum completion time of the jobs or makespan …

The problem addressed in this paper belongs to the topic of order scheduling, in which
customer orders–composed of different individual jobs–are scheduled so the objective …

This paper presents a hybrid Genetic-Bees Algorithm based optimised solution for the single
machine scheduling problem. The enhancement of the Bees Algorithm (BA) is conducted …

This paper addresses the problem of scheduling jobs in a flowshop layout where the
machines can operate at different speeds and require an amount of a resource that is a non …

In this paper, we focus on the solution of a hard single machine scheduling problem by new
heuristic algorithms embedding techniques from machine learning and scheduling theory …

In the context of smart buildings, house energy consumption plays a significant role in the
energy system. Since there are different billing rates, the aim of the smart grid system is to …

In this paper, we focus on the solution of a hard single machine scheduling problem by new
heuristic algorithms embedding techniques from machine learning field and scheduling …