Parallel Machine Scheduling Problem with a Resumable Availability Constraint

2014 ◽  
Vol 1061-1062 ◽  
pp. 708-711
Author(s):  
Qi Zhang ◽  
Cheng Xin Luo
Keyword(s):  
Parallel Machines ◽  
Approximation Scheme ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problem ◽  
Ordinary Sense ◽  
Polynomial Time Approximation Scheme ◽  
Approximation Solution ◽  
Availability Constraint ◽  
Parallel Machine Scheduling Problem

This paper considers a scheduling problem of two parallel machines with a resumable availability constraint. The objective is to minimize the makespan. The problem is NP-hard in the ordinary sense. Therefore, we need to find an approximate solution that fulfills the required error bound. To get a better approximation solution in a polynomial running time, we propose a fully polynomial-time approximation scheme (FPTAS) by trimming states space.

scholarly journals Parallel Machine Scheduling with Nested Processing Set Restrictions and Job Delivery Times

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Shuguang Li
Keyword(s):  
Parallel Machines ◽  
Approximation Scheme ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
List Scheduling ◽  
Polynomial Time Approximation Scheme ◽  
Time Approximation ◽  
Delivery Times ◽  
Specific Subset ◽  
Job Delivery

The problem of scheduling jobs with delivery times on parallel machines is studied, where each job can only be processed on a specific subset of the machines called its processing set. Two distinct processing sets are either nested or disjoint; that is, they do not partially overlap. All jobs are available for processing at time 0. The goal is to minimize the time by which all jobs are delivered, which is equivalent to minimizing the maximum lateness from the optimization viewpoint. A list scheduling approach is analyzed and its approximation ratio of 2 is established. In addition, a polynomial time approximation scheme is derived.

scholarly journals Online Algorithms for a Generalized Parallel Machine Scheduling Problem

MACRo 2015 ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 193-200
Author(s):  
István Szalkai ◽  
György Dósa
Keyword(s):  
Online Algorithms ◽  
Parallel Machines ◽  
Heuristic Algorithms ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
The Other ◽  
Workflow Scheduling ◽  
Scheduling Problem ◽  
Parallel Machine Scheduling Problem

AbstractWe consider different online algorithms for a generalized scheduling problem for parallel machines, described in details in the second section. This problem is the generalization of the classical parallel machine scheduling problem, when the makespan is minimized; in that case each job contains only one task. On the other hand, the problem in consideration is still a special version of the workflow scheduling problem. We present several heuristic algorithms and compare them by computer tests.

BicriteriaHeuristic for Unrelated Parallel Machine Scheduling Problem

2014 ◽  
Vol 1016 ◽  
pp. 824-828
Author(s):  
Yang Kuei Lin ◽  
Hao Chen Lin
Keyword(s):  
Parallel Machines ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Release Dates ◽  
Scheduling Problem ◽  
Unrelated Parallel Machines ◽  
Weighted Tardiness ◽  
Unrelated Parallel Machine Scheduling ◽  
Parallel Machine Scheduling Problem

In this research, a bi-criteria heuristic is proposed to find non-dominated solutions for scheduling unrelated parallel machines with release dates that minimizes makespan andtotal weighted tardiness.

scholarly journals IDENTICAL PARALLEL MACHINES SCHEDULING USING GENETIC ALGORITHM

2018 ◽  
Vol 18 (2) ◽  
pp. 321-330
Author(s):  
Aseel J Haleel
Keyword(s):  
Genetic Algorithm ◽  
Processing Time ◽  
Parallel Machines ◽  
Machine Scheduling ◽  
Setup Time ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problem ◽  
Identical Parallel Machine ◽  
Parallel Machine Scheduling Problem

Minimizing the scheduling production time consider one of the most important factors forcompanies which their objectives is achieve the maximum profits. This paper studies theidentical parallel machine scheduling problem which involves the assignment numbers ofjob (N) to set of identical parallel machine (M) in order to minimize the makespan(maximum completion time of all job). There are numerous troubles in solving the largesize of “parallel machine scheduling” problem with an excessive jobs and machines, sothe genetic algorithm was proposed in this paper which is consider an efficient algorithmthat fits larger size of identical “parallel machine scheduling” for minimizing themakespan. Most studies in the scheduling field suppose setup time is insignificant orincluded in the processing time, in this paper both the sequence independent setup timesand processing time were considered. The solutions of algorithms are coding in(MATLAB). A numerical example of (11) jobs are schedule on (3) machines todemonstrative the effectiveness of algorithm solution. The result show the algorithm caneffectively solve large size of scheduling problem and given the best schedule withminimum makespan.

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