vehicle routing problems
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Author(s):  
V. S. Vamsi Krishna Munjuluri ◽  
Yashwanth Reddy Telukuntla ◽  
Parimi Sanath Kumar ◽  
Aravind Mohan ◽  
Georg Gutjahr

Entropy ◽  
2021 ◽  
Vol 24 (1) ◽  
pp. 53
Author(s):  
Sebastián Muñoz-Herrera ◽  
Karol Suchan

Vehicle Routing Problems (VRP) comprise many variants obtained by adding to the original problem constraints representing diverse system characteristics. Different variants are widely studied in the literature; however, the impact that these constraints have on the structure of the search space associated with the problem is unknown, and so is their influence on the performance of search algorithms used to solve it. This article explores how assignation constraints (such as a limited vehicle capacity) impact VRP by disturbing the network structure defined by the solution space and the local operators in use. This research focuses on Fitness Landscape Analysis for the multiple Traveling Salesman Problem (m-TSP) and Capacitated VRP (CVRP). We propose a new Fitness Landscape Analysis measure that provides valuable information to characterize the fitness landscape’s structure under specific scenarios and obtain several relationships between the fitness landscape’s structure and the algorithmic performance.


Author(s):  
Hanguang Qiu ◽  
Cejun Cao ◽  
Jie Zhen ◽  
Hongyong Fu ◽  
Jixiang Zhou

A multicircle order acceptance strategy was proposed to decide whether to accept customer requests for specific last-mile delivery modes (including attended home or reception box delivery) and time slots. The strategy was composed of initializing acceptable time slot allocations, reallocating acceptable time slots, matching reference sites, and assessing time slot deviations. A strategy-oriented insertion algorithm for dynamic vehicle routing problems with hard time windows was constructed, thereby showing the proposed strategy achieves a better balance between revenue and distance than the “first come and first served” strategy. Always accepting global optimization result is not significantly better than adopting the result conditionally or based on simulated annealing theory. The distance and revenue gradually increase with the number of reference sites, while revenue/distance ratio decreases. The vehicles are available to serve more attended home delivery orders with a gradual increase in time slot interval, thereby leading to an increase of AHD and total revenue.


Author(s):  
Ehsan Khodabandeh ◽  
Lawrence V. Snyder ◽  
John Dennis ◽  
Joshua Hammond ◽  
Cody Wanless

We consider a broad family of vehicle routing problem variants with many complex and practical constraints, known as rich vehicle routing problems, which are faced on a daily basis by C.H. Robinson (CHR). Because CHR has many customers, each with distinct requirements, various routing problems with different objectives and constraints must be solved. We propose a novel framework for solving rich vehicle routing problems, which we demonstrate is effective in solving a variety of different problems. This framework, along with a simple user interface, has been wrapped into a new module and integrated into the company’s transportation planning and execution technology platform. Since its implementation, this new module has outperformed the previously used third-party technologies at CHR, significantly reduced setup times, and improved users’ productivity as well as customer outcomes.


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