scholarly journals A new efficient approach for solving the capacitated Vehicle Routing Problem using the Gravitational Emulation Local Search Algorithm

2017 ◽  
Vol 49 ◽  
pp. 663-679 ◽  
Author(s):  
Ali Asghar Rahmani Hosseinabadi ◽  
Najmeh Sadat Hosseini Rostami ◽  
Maryam Kardgar ◽  
Seyedsaeid Mirkamali ◽  
Ajith Abraham
2016 ◽  
Vol 29 (10) ◽  
pp. 955-968 ◽  
Author(s):  
Ali Asghar Rahmani Hosseinabadi ◽  
Javad Vahidi ◽  
Valentina Emilia Balas ◽  
Seyed Saeid Mirkamali

2008 ◽  
Vol 156 (11) ◽  
pp. 2050-2069 ◽  
Author(s):  
Toshihide Ibaraki ◽  
Shinji Imahori ◽  
Koji Nonobe ◽  
Kensuke Sobue ◽  
Takeaki Uno ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Weizhen Rao ◽  
Feng Liu ◽  
Shengbin Wang

The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.


2013 ◽  
Vol 859 ◽  
pp. 395-398
Author(s):  
Chun Yu Ren

This paper studies the vehicle routing problem. According to the characteristics of model, new tabu search algorithm is used to get the optimization solution. It applies newly improved insertion method to construct initial solution, to improve the feasibility of the solution; designs dual layered random operation to construct its neighborhood; applies auto adaptive tabu length to control the searching capability dynamically. At last, it uses simulated experiments to prove the effectiveness and feasibility of this algorithm, and provides clues for massively solving practical problems.


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