Research on Integrated Scheduling Model for Handling Operation System of Dry Bulk Cargo Port

2013 ◽  
Vol 12 (20) ◽  
pp. 5595-5600
Author(s):  
Kang Kai ◽  
Zhang Jing ◽  
Shang Cui-Juan ◽  
Yang Xiao-Xu
2010 ◽  
Vol 97-101 ◽  
pp. 2403-2406
Author(s):  
Ya Bo Luo ◽  
Ming Chun Tang

Grouping the similar processes is a good approach to improve the manufacturing efficiency, however, which is facing with two difficulties of the group automation and the constraints coupling. Regarding the numerical control (NC) machines and tasks as a grid system, this paper proposes a similarity-based tactic to solve the above difficulties. First, the methodology for analyzing the similarity among NC tasks is proposed to implement group automation taking the similarity principle as theory foundation. Second, based on the results drawn from the first step, the complex constraints including similarity constraints, delivery date constraints, and serial constraints are coupled to develop an integrated scheduling model. Finally, the integrated model is solved and the optimum solution is gotten using a specialized ants algorithm.


2011 ◽  
Vol 65 ◽  
pp. 99-103
Author(s):  
Xin Shun Tong ◽  
Li Hua Yang

Along with the market demand increasing, cigarette distribution center urgently needs to improve their working efficiency by reasonable storage modeal. This paper proposed an integrated scheduling model of automated high-rise warehouse combined with traditional flat storehouse, by planning the storage capacity in traditional flat storehouse and optimizing the storage spaces in automated high-rise warehouse, ensuring intelligent management while achieving flexible storage operations. This model effectively shortened the operating time compared to other storage models. Finally take Zhengzhou Cigarette Distribution Center as an example to analyze.


2019 ◽  
Vol 11 (19) ◽  
pp. 5144 ◽  
Author(s):  
Liang Gong ◽  
Yinzhen Li ◽  
Dejie Xu

Urban public transport is an effective way to solve urban traffic problems and promote sustainable development of urban traffic. A scientific operation scheduling system has an important guiding significance for optimizing the configuration of urban public transport capacity resources, improving the level of operation organization and management, and providing for the sustainability of the transportation system. According to the inhomogeneous distribution of passenger flow along transit lines, this study develops a combinational scheduling model in which the enterprise supplies zonal service based on regular service. The objective function minimizes the sum of passenger travel cost and operation cost, and the simulated annealing algorithm is designed to solve the optimization model. This paper abstracts an ideal example by taking a real-world case of Bus Line 131 in Lanzhou, China. The numerical example is used to verify the validity of the model and algorithm. Results show that the combinational operation scheme can effectively satisfy passengers’ demand and reduce the total cost by 7.03% in comparison with the regular operation system. The optimal combinational system with the lowest total cost can increase the vehicle load factor and improve the utilization ratio.


2011 ◽  
Vol 80-81 ◽  
pp. 1335-1339 ◽  
Author(s):  
You Long Lv ◽  
Gong Zhang ◽  
Jie Zhang ◽  
Yi Jun Dong

Job scheduling and AGV scheduling in FMS are regarded as two independent problems by most researchers. Their isolation ignores AGV’s use conflicts in the job scheduling and leads to low average equipment utilization. We point out the necessity for the job scheduling to integrate with AGV scheduling through analyzing scheduling problem of a specific type of FMS with single AGV and single buffer area. Then a corresponding mathematic model for integrated scheduling is presented based on the problem description and constraints for scheduling. A specific FMS is adopted to validate this integrated scheduling model. Based on data from this FMS, the model is performed through genetic algorithm with appropriate parameters. And job’s processing sequences as well as AGV’s moving path are obtained from the optimal gene order. The experiment result of this scheduling model adopting genetic algorithm shows good computing efficiency and equipment utilization.


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