On Index Structures in Hybrid Metaheuristics for Routing Problems with Hard Feasibility Checks: An Application to the 2-Dimensional Loading Vehicle Routing Problem

2010 ◽  
pp. 160-173 ◽  
Author(s):  
Johannes Strodl ◽  
Karl F. Doerner ◽  
Fabien Tricoire ◽  
Richard F. Hartl
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Index Structures ◽  
Hybrid Metaheuristics ◽  
Routing Problems ◽  
Routing Problem

scholarly journals Current State of Dynamic Vehicle Routing Problems Solved by Ant Colony Optimization Algorithm

2021 ◽  
Vol 15 (3) ◽  
pp. 429-434
Author(s):  
Luka Olivari ◽  
Goran Đukić
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Dynamic Vehicle Routing ◽  
Routing Problems ◽  
Routing Problem ◽  
Solution Methods

Dynamic Vehicle Routing Problem is a more complex version of Vehicle Routing Problem, closer to the present, real-world problems. Heuristic methods are used to solve the problem as Vehicle Routing Problem is NP-hard. Among many different solution methods, the Ant Colony Optimization algorithm is proven to be the efficient solution when dealing with the dynamic version of the problem. Even though this problem is known to the scientific community for decades, the field is extremely active due to technological advancements and the current relevance of the problem. As various sub-types of routing problems and solution methods exist, there is a great number of possible problem-solution combinations and research directions. This paper aims to make a focused review of the current state in the field of Dynamic Vehicle Routing Problems solved by Ant Colony Optimization algorithm, to establish current trends in the field.

scholarly journals Waste Collection Vehicle Routing Problem: Literature Review

2015 ◽  
Vol 27 (4) ◽  
pp. 345-358 ◽  
Author(s):  
Hui Han ◽  
Eva Ponce Cueto
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Research Literature ◽  
Arc Routing ◽  
Waste Collection ◽  
Logistics System ◽  
Routing Problems ◽  
Routing Problem ◽  
Node Routing

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP.

scholarly journals A New Plant Intelligent Behaviour Optimisation Algorithm for Solving Vehicle Routing Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Godfrey Chagwiza
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Future Research ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Optimisation Algorithm ◽  
Input Parameters ◽  
Problem Instances

A new plant intelligent behaviour optimisation algorithm is developed. The algorithm is motivated by intelligent behaviour of plants and is implemented to solve benchmark vehicle routing problems of all sizes, and results were compared to those in literature. The results show that the new algorithm outperforms most of algorithms it was compared to for very large and large vehicle routing problem instances. This is attributed to the ability of the plant to use previously stored memory to respond to new problems. Future research may focus on improving input parameters so as to achieve better results.

The Research of Vehicle Routing Problem With Time Window for Changsha Yunda Express in Kaifu District

2013 ◽  
Vol 336-338 ◽  
pp. 2525-2528
Author(s):  
Zhong Liu
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Distribution Center ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Service Levels ◽  
Shortest Distance

For express companies' distribution center, optimizing the vehicle routing can improve service levels and reduce logistics costs. This paper combines the present vehicle routing situation of Chang Sha Yunda Express in KaiFu area with the specific circumstances to analyze. A model of the vehicle routing problem with time window for the shortest distance was built and then use genetic algorithm to solve the problem. Its application showed that the method can effectively solve the current vehicle routing problems.

Hybrid Metaheuristics for the Vehicle Routing Problem with Stochastic Demands

2005 ◽  
Vol 5 (1) ◽  
pp. 91-110 ◽  
Author(s):  
Leonora Bianchi ◽  
Mauro Birattari ◽  
Marco Chiarandini ◽  
Max Manfrin ◽  
Monaldo Mastrolilli ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Metaheuristics ◽  
Routing Problem ◽  
Stochastic Demands

scholarly journals Multiple Ant Colony Optimization for Single Depot Multiple Trip Vehicle Routing Problems

10.29007/8tjs ◽  
2018 ◽  
Author(s):  
Zhengmao Ye ◽  
Habib Mohamadian
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Urban Areas ◽  
Ant Colony ◽  
Ant Colony System ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Single Vehicle

The multiple trip vehicle routing problem involves several sequences of routes. Working shift of single vehicle can be scheduled in multiple trips. It is suitable for urban areas where the vehicle has very limited size and capacity over short travel distances. The size and capacity limit also requires the vehicle should be vacated frequently. As a result, the vehicle could be used in different trips as long as the total time or distance is not exceeded. Various approaches are developed to solve the vehicle routing problem (VRP). Except for the simplest cases, VRP is always a computationally complex issue in order to optimize the objective function in terms or both time and expense. Ant colony optimization (ACO) has been introduced to solve the vehicle routing problem. The multiple ant colony system is proposed to search for alternative trails between the source and destination so as to minimize (fuel consumption, distance, time) among numerous geographically scattered routes. The objective is to design adaptive routing so as to balance loads among congesting city networks and to be adaptable to connection failures. As the route number increases, each route becomes less densely packed. It can be viewed as the vehicle scheduling problem with capacity constraints. The proposed scheme is applied to typical cases of vehicle routing problems with a single depot and flexible trip numbers. Results show feasibility and effectiveness of the approach.

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