An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem

2014 ◽  
Vol 239 (2) ◽  
pp. 413-426 ◽  
Author(s):  
Deniz Aksen ◽  
Onur Kaya ◽  
F. Sibel Salman ◽  
Özge Tüncel
Keyword(s):  
Search Algorithm ◽  
Neighborhood Search ◽  
Inventory Routing ◽  
Large Neighborhood Search ◽  
Adaptive Large Neighborhood Search ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Large Neighborhood ◽  
Neighborhood Search Algorithm

scholarly journals An Adaptive Large Neighborhood Search Algorithm for the Satellite Data Transmission Scheduling Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yingguo Chen ◽  
Ming Chen ◽  
Jun Wen ◽  
Yingwu Chen ◽  
Wen Xiang
Keyword(s):  
Satellite Data ◽  
Data Transmission ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Transmission Scheduling ◽  
Large Neighborhood Search ◽  
Adaptive Large Neighborhood Search ◽  
Large Neighborhood ◽  
Ground Station ◽  
Neighborhood Search Algorithm

Satellite establishes a satellite ground station to satellite link with a ground station to complete data transmission. However, in China, satellite ground stations only exist within the country. With the rapid increase in the number of satellites, effectively dispatching satellite communications and maximizing the performance of ground stations are necessary. We propose a heuristic adaptive large neighborhood search algorithm (H-ALNS) to solve the satellite data transmission scheduling (SDTS) problem. The algorithm includes two heuristic rules for generating the initial scheme and the conflict reduction process after updating the neighborhood. A heuristic task assignment method is used to select the execution time window and position for the task sequence. The adaptive operator is used to update the delete operator and insert operator weights into the H-ALNS. The quality of the generated planning scheme improved through continuous neighborhood destruction and repair. Through experimental analysis, the algorithm we propose is feasible for solving SDTS problems and surpasses the planning results acquired using other comparison algorithms. The H-ALNS has good prospects for practical engineering applications.

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