An Improved Simulated Annealing Algorithm for Real-Time Dynamic Job-Shop Scheduling

2011 ◽  
Vol 186 ◽  
pp. 636-639 ◽  
Author(s):  
Yan Cao ◽  
Jiang Du
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Combinatorial Problem ◽  
Manufacturing Execution System ◽  
Scheduling Problems ◽  
Time Dynamic ◽  
Shop Scheduling

Job-shop scheduling is one of the core research aspects of Manufacturing Execution System (MES). It is significant for improving the utilization of enterprise resources, enhancing product quality, shortening delivery periods, reducing product cost, and raising enterprise competitive power in market economy. In order to solve this problem, Simulated Annealing (SA) algorithm is improved to solve large-scale combinatorial problem of job-shop scheduling. To make the SA algorithm more effective to solve job-shop scheduling problems, a solution encoding mode, scheduling scheme generation, initial temperature selection, temperature updating function, Markov chain length, end rule, and so on of the improved SA algorithm are discussed that affect the computation speed and convergence of the SA algorithm. Finally, the improved SA algorithm is validated by a job–shop scheduling problem of 10 workpieces and 10 machines.

scholarly journals Cooperative Threads with Effective-Address in Simulated Annealing Algorithm to Job Shop Scheduling Problems

2019 ◽  
Vol 9 (16) ◽  
pp. 3360 ◽  
Author(s):  
Marco Antonio Cruz-Chávez ◽  
Jesús del C. Peralta-Abarca ◽  
Martín H. Cruz-Rosales
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Distributed Processing ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Parallel And Distributed Processing ◽  
Annealing Algorithm ◽  
Cooperative Algorithm

This paper presents a parallel algorithm applied to the job shop scheduling problem (JSSP). The algorithm generates a set of threads, which work in parallel. Each generated thread, executes a procedure of simulated annealing which obtains one solution for the problem. Each solution is directed towards the best solution found by the system at the present, through a procedure called effective-address. The cooperative algorithm evaluates the makespan for various benchmarks of different sizes, small, medium, and large. A statistical analysis of the results of the algorithm is presented and a comparison of performance with other (sequential, parallel, and distributed processing) algorithms that are found in the literature is presented. The obtained results show that the cooperation of threads carried out by means of effective-address procedure permits to simulated annealing to work with increased efficacy and efficiency for problems of JSSP.

System Development of a Simulated Annealing Algorithm for Job-Shop Scheduling Problem Based on Delphi

2011 ◽  
Vol 411 ◽  
pp. 411-414
Author(s):  
Yan Cao ◽  
Sen Cao ◽  
Lei Lei ◽  
Yu Bai ◽  
Lei Shi
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Production Cycle ◽  
Scheduling Problem ◽  
Manufacturing Execution System ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Combinatorial Optimization Problems

The job-shop scheduling is the key element of a manufacturing execution system (MES). It is significant for enterprises to utilize resources rationally, enhance product quality, shorten production cycle, reduce production cost, and improve its market competitiveness. In the paper, Simulated Annealing (SA) algorithm is adopted to solve the job-shop scheduling problem. SA algorithm is a random search method proposed to solve large-scale combinatorial optimization problems. As an efficient and general method, the optimization and convergence performance of SA algorithm is mainly affected by the problem and several factors. In order to facilitate use’s employment, a job-shop scheduling system based on SA algorithm is developed using Delphi. The system developed is verified by an example. The results show that it is an effective solution to the job-shop scheduling problems.

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