Router: A Fast and Flexible Local Search Algorithm for a Class of Rich Vehicle Routing Problems

2005 ◽  
pp. 144-149 ◽  
Author(s):  
Ulrich Derigs ◽  
Thomas Döhmer
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Search Algorithm ◽  
Vehicle Routing Problems ◽  
Local Search Algorithm ◽  
Routing Problems

An Iterated Local Search Algorithm for Fuel Consumption Optimization of Vehicle Routing Problems

2011 ◽  
Vol 148-149 ◽  
pp. 1248-1251
Author(s):  
Xu Dong Wu
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Fuel Consumption ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Vehicle Routing Problems ◽  
Local Search Algorithm ◽  
Routing Problems ◽  
Combinatorial Optimization Problems

The iterated local search algorithm has been widely used in combinatorial optimization problems. A new fuel consumption objective for the vehicle routing problems was presented in this paper. A fuel consumption modal of the vehicle load is introduced and an improved iterated local search algorithm is used for the problem. An initial solution is generated by the Solomon I1 algorithm, and then the iterated local search algorithm is proposed for the fuel consumption optimization.

scholarly journals Novel Encoding and Routing Balance Insertion Based Particle Swarm Optimization with Application to Optimal CVRP Depot Location Determination

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ruey-Maw Chen ◽  
Yin-Mou Shen
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Vehicle Routing ◽  
Particle Swarm ◽  
Transportation Cost ◽  
Vehicle Routing Problems ◽  
Solution Quality ◽  
Swarm Optimization ◽  
Routing Problems ◽  
Vehicle Routes

A depot location has a significant effect on the transportation cost in vehicle routing problems. This study proposes a hierarchical particle swarm optimization (PSO) including inner and outer layers to obtain the best location to establish a depot and the corresponding optimal vehicle routes using the determined depot location. The inner layer PSO is applied to obtain optimal vehicle routes while the outer layer PSO is to acquire the depot location. A novel particle encoding is suggested for the inner layer PSO, the novel PSO encoding facilitates solving the customer assignment and the visiting order determination simultaneously to greatly lower processing efforts and hence reduce the computation complexity. Meanwhile, a routing balance insertion (RBI) local search is designed to improve the solution quality. The RBI local search moves the nearest customer from the longest route to the shortest route to reduce the travel distance. Vehicle routing problems from an operation research library were tested and an average of 16% total routing distance improvement between having and not having planned the optimal depot locations is obtained. A real world case for finding the new plant location was also conducted and significantly reduced the cost by about 29%.

OVRP_GELS: solving open vehicle routing problem using the gravitational emulation local search algorithm

2016 ◽  
Vol 29 (10) ◽  
pp. 955-968 ◽  
Author(s):  
Ali Asghar Rahmani Hosseinabadi ◽  
Javad Vahidi ◽  
Valentina Emilia Balas ◽  
Seyed Saeid Mirkamali
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Local Search Algorithm ◽  
Routing Problem ◽  
Open Vehicle Routing Problem ◽  
Open Vehicle Routing

scholarly journals An iterated local search algorithm for the vehicle routing problem with convex time penalty functions

2008 ◽  
Vol 156 (11) ◽  
pp. 2050-2069 ◽  
Author(s):  
Toshihide Ibaraki ◽  
Shinji Imahori ◽  
Koji Nonobe ◽  
Kensuke Sobue ◽  
Takeaki Uno ◽  
...  
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Penalty Functions ◽  
Local Search Algorithm ◽  
Routing Problem

scholarly journals An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Weizhen Rao ◽  
Feng Liu ◽  
Shengbin Wang
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Fuel Consumption ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Classical Model ◽  
Mixed Integer ◽  
Local Search Algorithm ◽  
Routing Problem ◽  
Total Vehicle

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.

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