Multi Machine Scheduling

A robust optimal scheduling method driven by multi-objects is proposed for the collaborative optimization problem between dynamic scheduling, preventive maintenance of equipment, and robustness of

Machine scheduling, in particular, refers to problems in a manufacturing environment where jobs have to be scheduled for processing on one or more machines to optimize one or more objectives. By means of doctoral research at the ORampS group, several machine scheduling problems, ranging from the single machine environment to the multi-stage

In the context of job scheduling in parallel machines, we present a class of binary programs for the minimization of the -norm of completion time variances a flexible measure of homogeneity in multi-machine job processing.Building on overlooked properties of the min completion time variance in a single machine and on an equivalent bilevel formulation, our approach provides asymptotic

Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fullled, is a ubiquitousand complexactivityineveryday life. Thispaperpresents an ap-proach to multi-machine scheduling that follows the multi-

methods can be divided into single-machine scheduling and multi-machine scheduling depending on the number of machines.368 are examples of single-machine scheduling methods that can design schedules for the shortest work time or shortest lead time.In contrast, multimachine scheduling methods can make schedules based on two concepts -

This paper addresses the problem of scheduling n equal-processing-time jobs with release dates non-preemptively on identical machines to optimize two criteria simultaneously or hierarchically. For simultaneous optimization of total completion time and makespan and maximum cost, an algorithm is presented which can produce all Pareto-optimal points together with the corresponding schedules

Since very few multi-operation scheduling problems can be solved in polynomial time, adding the multi-machine en-vironment makes the resulting multi-operation multi-machine scheduling even more difcult. In this paper, we study an open-shop scheduling problem with two shops and k identical parallel machines in each shop to minimize the makespan.

The multi-machine collaborative operation mode, where multiple agricultural machines work in the plots, has become the focus of research on unmanned farms and regional farmland machinery operations, especially in terms of unmanned operation and scheduling management of agricultural machinery equipment Karunathilake et al., 2023, Yousaf et al

View a PDF of the paper titled Deep Reinforcement Learning for Multi-Resource Multi-Machine Job Scheduling, by Weijia Chen and 2 other authors. View PDF Abstract Minimizing job scheduling time is a fundamental issue in data center networks that has been extensively studied in recent years. The incoming jobs require different CPU and memory

In the vast majority of the considered in the literature scheduling problems, it is assumed that a task is done on a single machine. However, in many real production processes, in particular - modern computational systems - a task execution requires the use of more than one machine CPU, Boejko et al. .Then, we can talk about systems with parallel machines and multi-machine