scholarly journals Data-Driven Bus Route Optimization Algorithm under Sudden Interruption of Public Transport

IEEE Access ◽  
2022 ◽  
pp. 1-1
Author(s):  
Ruisong Liu ◽  
Ning Wang
Keyword(s):  
Optimization Algorithm ◽  
Public Transport ◽  
Route Optimization ◽  
Data Driven

scholarly journals An Optimization Model for Construction Stage and Zone Plans of Rockfill Dams Based on the Enhanced Whale Optimization Algorithm

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 466 ◽  
Author(s):  
Jun Zhang ◽  
Denghua Zhong ◽  
Mengqi Zhao ◽  
Jia Yu ◽  
Fei Lv
Keyword(s):  
Optimization Algorithm ◽  
Optimization Model ◽  
Large Scale ◽  
Flow Shop ◽  
Whale Optimization Algorithm ◽  
Data Driven ◽  
Construction Stage ◽  
Construction Scheme ◽  
Rockfill Dam ◽  
Whale Optimization

Rockfill dams are among the most complex, significant, and costly infrastructure projects of great national importance. A key issue in their design is the construction stage and zone optimization. However, a detailed flow shop construction scheme that considers the opinions of decision makers cannot be obtained using the current rock-fill dam construction stage and zone optimization methods, and the robustness and efficiency of existing construction stage and zone optimization approaches are not sufficient. This research presents a construction stage and zone optimization model based on a data-driven analytical hierarchy process extended by D numbers (D-AHP) and an enhanced whale optimization algorithm (EWOA). The flow shop construction scheme is optimized by presenting an automatic flow shop construction scheme multi-criteria decision making (MCDM) method, which integrates the data-driven D-AHP with an improved construction simulation of a high rockfill dam (CSHRD). The EWOA, which uses Levy flight to improve the robustness and efficiency of the whale optimization algorithm (WOA), is adopted for optimization. This proposed model is implemented to optimize the construction stages and zones while obtaining a preferable flow shop construction scheme. The effectiveness and advantages of the model are proven by an example of a large-scale rockfill dam.

The Improved Route Optimization Based on Hybrid Optimization Algorithm Based on GA and TS

2012 ◽  
Vol 170-173 ◽  
pp. 3695-3698
Author(s):  
Jun Ma ◽  
Li Ying Zhang
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Route Optimization ◽  
Hybrid Optimization ◽  
Improved Genetic Algorithm ◽  
Hybrid Optimization Algorithm ◽  
Search Speed

The vehicle routing planning in the process of logistics is a hot issue. There is a lack of traditional genetic algorithm used to solve this issue, so the taboos is introduced to improve it. The improved genetic algorithm based on taboos get high-search speed compared to the traditional genetic algorithm, and this improvement is verified by the example.

scholarly journals Improving Efficiency of Volunteer-Based Food Rescue Operations

2020 ◽  
Vol 34 (08) ◽  
pp. 13369-13375
Author(s):  
Zheyuan Ryan Shi ◽  
Yiwen Yuan ◽  
Kimberly Lo ◽  
Leah Lizarondo ◽  
Fei Fang
Keyword(s):  
Food Insecurity ◽  
High Precision ◽  
Branch And Bound ◽  
Food Waste ◽  
Optimization Algorithm ◽  
Data Driven ◽  
Data Generation ◽  
Rescue Operation ◽  
Optimal Intervention ◽  
Near Future

Food waste and food insecurity are two challenges that coexist in many communities. To mitigate the problem, food rescue platforms match excess food with the communities in need, and leverage external volunteers to transport the food. However, the external volunteers bring significant uncertainty to the food rescue operation. We work with a large food rescue organization to predict the uncertainty and furthermore to find ways to reduce the human dispatcher's workload and the redundant notifications sent to volunteers. We make two main contributions. (1) We train a stacking model which predicts whether a rescue will be claimed with high precision and AUC. This model can help the dispatcher better plan for backup options and alleviate their uncertainty. (2) We develop a data-driven optimization algorithm to compute the optimal intervention and notification scheme. The algorithm uses a novel counterfactual data generation approach and the branch and bound framework. Our result reduces the number of notifications and interventions required in the food rescue operation. We are working with the organization to deploy our results in the near future.

scholarly journals SCAN PLANNING AND ROUTE OPTIMIZATION FOR CONTROL OF EXECUTION OF AS-DESIGNED BIM

2018 ◽  
Vol XLII-4 ◽  
pp. 143-148 ◽  
Author(s):  
L. Díaz-Vilariño ◽  
E. Frías ◽  
J. Balado ◽  
H. González-Jorge
Keyword(s):  
Optimization Algorithm ◽  
Point Cloud ◽  
Processing Time ◽  
Travelling Salesman Problem ◽  
Route Optimization ◽  
Optimal Route ◽  
Ant Colony Optimization Algorithm ◽  
Travelling Salesman ◽  
Tracing Algorithm ◽  
Grid Based

<p><strong>Abstract.</strong> Scan-to-BIM systems have been recently proposed for the dimensional and quality assessment of as-built construction components with planned works. The procedure is generally based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models. A major concern in Scan-to-BIM procedures is point cloud quality in terms of data completeness and consequently, the scanning process should be designed in order to obtain a full coverage of the scene while avoiding major occlusions. This work proposes a method to optimize the number and scan positions for Scan-to-BIM procedures following stop &amp;amp; go scanning. The method is based on a visibility analysis using a <i>ray-tracing algorithm</i>. In addition, the optimal route between scan positions is formulated as a <i>travelling salesman problem</i> and solved using a suboptimal <i>ant colony optimization algorithm</i>. The distribution of candidate positions follows a grid-based structure, although other distributions based on triangulation or tessellation can be implemented to reduce the number of candidate positions and processing time.</p>

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