scholarly journals Research on Vehicle Routes Optimization for Emergency Materials Distribution

2020 ◽  
Vol 1622 ◽  
pp. 012075
Author(s):  
Jiashan Zhang ◽  
Xiaoqun Lin
Keyword(s):  
Vehicle Routes

Smart Design of Driverless-Vehicle Routes in the Arctic and Far North

2018 ◽  
Vol 38 (10) ◽  
pp. 769-772
Author(s):  
Yu. G. Kabaldin ◽  
D. A. Shatagin ◽  
A. V. Kiselev ◽  
M. V. Zhelonkin ◽  
A. A. Golovin
Keyword(s):  
The Arctic ◽  
Far North ◽  
Vehicle Routes

A Precast Road Panel Structure for Heavy Vehicles

2014 ◽  
Vol 627 ◽  
pp. 257-261
Author(s):  
Hu Qi ◽  
Yun Gui Li ◽  
Kang Liu
Keyword(s):  
Heavy Traffic ◽  
Test Results ◽  
Heavy Vehicles ◽  
Experiment Research ◽  
Structure System ◽  
Vehicle Routes

A composite precast road panel structure system suitable for heavy vehicles is put forward, which combined by two layers of composite stagger-jointed road panel. Experiment research are adopted to study the proposed road panel structure and common road panel structure respectively. In order to research the proposed road panel structure performance under heavy vehicles, five different cases are studied in experiment each which different vehicle routes. The test results show that the proposed one can reduce 24.2% to 46.4% ( an average of 35% ) of the subgrade stress in five cases so as to reduce the subgrade damage under driving heavy traffic.

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%.

scholarly journals VEHICLE ROUTING PROBLEM WITH TIME WINDOWS USING HYBRID ENCODING GENETIC ALGORITHM

2014 ◽  
Vol 12 (10) ◽  
pp. 3945-3951
Author(s):  
Dr P.K Chenniappan ◽  
Mrs.S.Aruna Devi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Minimal Cost ◽  
Total Size ◽  
Routing Problem ◽  
Time Window Constraints ◽  
Vehicle Capacity ◽  
Vehicle Routes

The vehicle routing problem is to determine K vehicle routes, where a route is a tour that begins at the depot, traverses a subset of the customers in a specified sequence and returns to the depot. Each customer must be assigned to exactly one of the K vehicle routes and total size of deliveries for customers assigned to each vehicle must not exceed the vehicle capacity. The routes should be chosen to minimize total travel cost. Thispapergivesasolutiontofindanoptimumrouteforvehicle routingproblem using Hybrid Encoding GeneticAlgorithm (HEGA)technique tested on c++ programming.The objective is to find routes for the vehicles to service all the customers at a minimal cost and time without violating the capacity, travel time constraints and time window constraints

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