An improved chaos immune algorithm based on Hadoop framework to solve job-shop scheduling problem

2013 ◽  
Author(s):  
Xu Liang ◽  
Minyi Wang ◽  
Xuan Jiao ◽  
Ming Huang
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Immune Algorithm ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Hadoop Framework

Job-Shop Scheduling Method Based on Modified Immune Algorithm

2006 ◽  
Vol 315-316 ◽  
pp. 481-485 ◽  
Author(s):  
W.L. Wang ◽  
X.L. Xu ◽  
Yan Wei Zhao ◽  
Q. Guan
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Immune Algorithm ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Adaptive Process ◽  
Automatic Pattern Recognition ◽  
Scheduling Method ◽  
Simulation Results

The mechanism of vaccination was analyzed in the immune system and the improved immune algorithm for the job-shop scheduling problem was presented. The proposed method can reserve the advantage of vaccination and it is independent of the initial antibodies. Especially, the adaptive process of vaccination with the automatic pattern recognition can not only quicken the convergence of the algorithm but also overcome some deficiencies in distilling manually the transcendent knowledge of the problem. Simulation results show that it is an effective approach.

scholarly journals PENYELESAIAN MULTI-OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM MENGGUNAKAN HYBRID ALGORITMA IMUN

2017 ◽  
Vol 6 (2) ◽  
pp. 79
Author(s):  
Yabunayya Habibi ◽  
Galandaru Swalaganata ◽  
Aprilia Divi Yustita
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Immune Algorithm ◽  
Local Optimum ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective

Flexible Job shop scheduling problem (FJSSP) is one of scheduling problems with specification: there is a job to be done in a certain order, each job contains a number of operations and each operation is processed on a machine of some available machine. The purpose of this paper is to solve Multi-objective Flexible Job Shop scheduling problem with minimizing the makespan, the biggest workload and the total workload of all machines. Because of complexity these problem, a integrated approach Immune Algorithm (IA) and Simulated Annealing (SA) algorithm are combined to solve the multi-objective FJSSP. A clonal selection is a strategy for generating new antibody based on selecting the antibody for reproduction. SA is used as a local search search algorithm for enhancing the local ability with certain probability to avoid becoming trapped in a local optimum. The simulation result have proved that this hybrid immune algorithm is an efficient and effective approach to solve the multi-objective FJSSP

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