A Newton-based heuristic algorithm for multi-objective flexible job-shop scheduling problem

2014 ◽  
Vol 27 (2) ◽  
pp. 409-416 ◽  
Author(s):  
Miguel A. Fernández Pérez ◽  
Fernanda M. P. Raupp
Keyword(s):  
Heuristic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective

Introducing an effective meta-heuristic algorithm: Cosmogony algorithm (CA)

2020 ◽  
Vol 39 (3) ◽  
pp. 3475-3501
Author(s):  
Nasser Shahsavari-Pour ◽  
Hamed Mohammadi-Andargoli ◽  
Najmeh Bahram-Pour
Keyword(s):  
Heuristic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
The Other ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective

The purpose of this paper is to introduce a new meta-heuristic algorithm and apply this for solving a multi-objective flexible job-shop scheduling problem. The name of this algorithm is Cosmogony (CA). This algorithm has inspired by the ecosystem process of creatures and their environment. For a better understanding, we make an effort to apply the concepts of the meta-heuristic algorithms up to a possible extent. This algorithm identifies local optimal points during the self-search process of problem-solving. Initial creatures have been generated randomly in a certain number. This algorithm incorporates many features of the other algorithms in itself. So that to prove the ability and efficiency of CA, a flexible job-shop scheduling problem has surveyed. This problem is in a Non-resumable situation with maintenance activity constraints in a two-time fixed and non-fixed state. The algorithm performance is evaluated by numerical experiments. The result has shown the proposed approach is more efficient and appropriate than the other methods. It also has high power in the searching process in the feasible region of the multi-objective flexible job-shop scheduling problem and high converge power.

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