Minimizing job completion time variance for service stability on identical parallel machines

2010 ◽  
Vol 58 (4) ◽  
pp. 729-738 ◽  
Author(s):  
Xueping Li ◽  
Yuerong Chen ◽  
Yang Sun
Keyword(s):  
Completion Time ◽  
Parallel Machines ◽  
Identical Parallel Machines ◽  
Time Variance

SEMI-ONLINE MACHINE COVERING

2007 ◽  
Vol 24 (03) ◽  
pp. 373-382 ◽  
Author(s):  
SHENG-YI CAI
Keyword(s):  
Competitive Ratio ◽  
Completion Time ◽  
Online Algorithm ◽  
Parallel Machines ◽  
Identical Parallel Machines ◽  
Processing Times ◽  
First Case ◽  
Machine Covering

This paper investigates two different semi-online versions of the machine covering, which is the problem of assigning a set of jobs to a system of m(m ≥ 3) identical parallel machines so as to maximize the earliest machine completion time. In the first case, we assume that the largest processing times is known in advance. In the second case, we assume that the total processing times of all jobs is known in advance. For each version we propose a semi-online algorithm and investigate its competitive ratio. The competitive ratio of each algorithm is [Formula: see text], which is shown to be the best possible competitive ratio for each semi-online problem.

Hybrid Multi-Objective Methods to Solve Reentrant Shops

2012 ◽  
Vol 3 (4) ◽  
pp. 15-32
Author(s):  
Frédéric Dugardin ◽  
Farouk Yalaoui ◽  
Lionel Amodeo
Keyword(s):  
Local Search ◽  
Design Of Experiment ◽  
Completion Time ◽  
Parallel Machines ◽  
Flow Shop ◽  
Hybrid Flow Shop ◽  
Identical Parallel Machines ◽  
Multi Objective ◽  
Local Searches ◽  
Maximum Completion Time

This article examines the multi-objective scheduling of a reentrant hybrid flow shop. This type of shop is composed of several stages made of several identical parallel machines. When a task has to be processed on a stage, it is assigned to the machine with the smallest workload. This problem shows a reentrant structure: each task must be processed several times at each stage. In this paper, this problem is solved by minimizing two objectives: the makespan (maximum completion time of the jobs) and the total tardiness of the tasks. A new method is improved with different local searches: Adjacent and Non Adjacent Pairwise Interchange, Extract and Backward-Shifted Reinsertion, and Extract and Forward-Shifted Reinsertion. Every local search is tuned with statistical method (design of experiment) and the best one is worked out. This method is compared with the best one in several instances. The results involve three different measures.

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