Auction-based approach to the job-shop problem with parallel batch processing and a machine availability constraint

2021 ◽  
pp. 1-18
Author(s):  
Chengkuan Zeng ◽  
Zixuan Liu ◽  
Jiafu Tang ◽  
Zhi-Ping Fan ◽  
Chongjun Yan
Keyword(s):  
Job Shop ◽  
Batch Processing ◽  
Availability Constraint ◽  
Machine Availability

Heuristics for Job Shop Scheduling With Limited Machine Availability

2012 ◽  
Vol 45 (6) ◽  
pp. 1395-1400 ◽  
Author(s):  
Sadia Azem ◽  
Riad Aggoune ◽  
Stéphane Dauzère-Pérès
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Shop Scheduling ◽  
Machine Availability

scholarly journals Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
M. Frutos ◽  
M. Méndez ◽  
F. Tohmé ◽  
D. Broz
Keyword(s):  
Buffer Capacity ◽  
Job Shop ◽  
Production Systems ◽  
Pareto Frontier ◽  
Multiobjective Evolutionary Algorithms ◽  
Machine Availability ◽  
Operations Scheduling ◽  
Performance Indexes ◽  
Availability Constraints ◽  
Multiobjective Algorithms

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.

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