LU matrix key pre-distribution scheme with authentication

The job-shop scheduling problem (JSP) is a hard combinatorial optimization problem. In this paper, the mixed programming of MATLAB and VC is considered to solve the JSP. Firstly, MATLAB is used to implement an improved genetic algorithm (GA), and then the program is packaged into a dynamic link library (DLL). Secondly, VC is used to realize the input/output interface and call the GA DLL to schedule and store the scheduling results into the ORACLE database. Finally, the simulation results show that the improved GA has good optimization performance in solving JSP and the mixed programming design is effective. IndexTerms -Job-shop Scheduling Problem (JSP), Genetic Algorithm (GA), Scheduling Optimization, Mixed Programming of MATLAB and VC++.

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The Research of Resource Scheduling Based on Genetic Algorithm

Yuan

Yang

2012

KEM

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Job Shop scheduling problem, the essence of which is the resources scheduling problem, which has been proved to be a complete NP-hard problem. It has importantly realistic effect on further research, and has become a hot spot of research now. According to the practical Job Shop, as equipment resources are not unique, there are several machine tools with high frequency, while the number of that of low frequency is only one; the working procedure of processing components are also quite different, so we have put forward the Genetic Algorithm considering the sequence and, simultaneously, the machine choice. For reaching the shortest producing period, this method adopts Gemini string to encode, combining with the characteristics of the resources scheduling problem, and designs the unique way of Crossover and Mutation, meanwhile, it shows that the algorithm is effective through a specific example simulation analysis.

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LU matrix key pre-distribution scheme with authentication

Cited by 3 publications

References 3 publications

Gaussian-Heimite in the Atom Population Solution

Gaussian-Heimite in the Atom Population Solution

Job-shop scheduling optimization design based on an improved GA

The Research of Resource Scheduling Based on Genetic Algorithm

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