scholarly journals Evaluating the neighborhood, hybrid and reversion search techniques of a simulated annealing algorithm in solving forest spatial harvest scheduling problems

Silva Fennica ◽  
2016 ◽  
Vol 50 (4) ◽  
Author(s):  
Lingbo Dong ◽  
Pete Bettinger ◽  
Zhaogang Liu ◽  
Huiyan Qin ◽  
Yinghui Zhao
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Scheduling Problems ◽  
Harvest Scheduling ◽  
Search Techniques ◽  
Annealing Algorithm

scholarly journals Scheduling Optimization of Sugarcane Harvest Using Simulated Annealing Algorithm

2018 ◽  
Vol 5 (2) ◽  
pp. 138-147
Author(s):  
Eka Nur Afifah ◽  
Alamsyah Alamsyah ◽  
Endang Sugiharti
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Planning Process ◽  
Search Algorithm ◽  
Raw Material ◽  
Local Search Algorithm ◽  
Harvest Scheduling ◽  
Actual Result ◽  
Material Supply ◽  
Annealing Algorithm

Scheduling is one of the important part in production planning process. One of the factor that influence the smooth production process is raw material supply. Sugarcane supply as the main raw material in the making of sugar is the most important componen. The algorithm that used in this study was Simulated Annealing (SA) algorithm. SA apability to accept the bad or no better solution within certain time distinguist it from another local search algorithm. Aim of this study was to implement the SA algorithm in scheduling the sugarcane harvest process so that the amount of sugarcane harvest not so differ from mill capacity of the factory. Data used in this study were 60 data from sugarcane farms that ready to cut and mill capacity 1660 tons. Sugarcane harvest process in 19 days producing 33043,76 tons used SA algorithm and 27089,47 tons from factory actual result. Based on few experiments, obtained sugarcane harvest average by SA algorithm was 1651,63 tons per day and factory actual result was 1354,47 tons. Result of harvest scheduling used SA algorithm showed not so differ average from mill capacity of factory. Truck uses scheduling by SA algorithm showed average 119 trucks per day while from factory actual result was 156 trucks. With the same harvest time, SA algorithm result was greater  and the amount of used truck less than actual result of factory. Thus, can be concluded SA algorithm can make the scheduling of sugarcane harvest become more optimall compared to other methods applied by the factory nowdays.

scholarly journals Research on Flexible Equipment Maintenance Process Scheduling Problems Based on HNSGSA Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Weixing Song ◽  
Jianshe Kang ◽  
Jingjing Wu ◽  
Hui Jia ◽  
Huiqiang Chang
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Simulated Annealing Algorithm ◽  
Equipment Maintenance ◽  
Scheduling Problems ◽  
Process Scheduling ◽  
Nsga Ii ◽  
Maintenance Work ◽  
Annealing Algorithm ◽  
Maintenance Process

The characteristics of military equipment maintenance work are analyzed. According to the actual needs of the army, the optimization objective is designed, and a multiobjective flexible maintenance process optimization model is built based on the maintenance business organization process. Combining the advantages of NSGA-II algorithm and the simulated annealing algorithm, this paper proposes a novel improved HNSGSA algorithm, of which algorithm flow is detailed. In accordance with the requirements of the optimization model, this paper also specifically designs the coding methods of the process sequence, the equipment selection and the process scheduling, and the corresponding cross mutation method. The feasibility of the built model is verified by the actual data of maintenance business. And, the superiority, accuracy, and effectiveness of the proposed algorithm are further validated by the comparison with the NSGA-II algorithm and the simulated annealing algorithm, providing a scientific reference for the army to carry out equipment maintenance.

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