HYBRIDIZING ANT COLONY SYSTEMS AND TABU SEARCH FOR A VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

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On the Performance of Tabu Search Algorithm for the Vehicle Routing Problem with Time Windows

2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) ◽

10.1109/w-ficloud.2016.77 ◽

2016 ◽

Cited By ~ 5

Author(s):

Pinar Kirci

Keyword(s):

Tabu Search ◽

Vehicle Routing ◽

Vehicle Routing Problem ◽

Search Algorithm ◽

Time Windows ◽

Tabu Search Algorithm ◽

Routing Problem

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A heuristic approach and a tabu search for the heterogeneous multi-type fleet vehicle routing problem with time windows and an incompatible loading constraint

Computers & Industrial Engineering ◽

10.1016/j.cie.2014.11.004 ◽

2015 ◽

Vol 89 ◽

pp. 162-176 ◽

Cited By ~ 20

Author(s):

Zheng Wang ◽

Ying Li ◽

Xiangpei Hu

Keyword(s):

Tabu Search ◽

Vehicle Routing ◽

Vehicle Routing Problem ◽

Time Windows ◽

Heuristic Approach ◽

Routing Problem

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Optimization of Multi-Depot Heterogeneous Incident Vehicle Routing Problem with Soft Time Windows Based on an Improved Ant Colony Optimization

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1061-1062.1108 ◽

2014 ◽

Vol 1061-1062 ◽

pp. 1108-1117

Author(s):

Ya Lian Tang ◽

Yan Guang Cai ◽

Qi Jiang Yang

Keyword(s):

Ant Colony Optimization ◽

Vehicle Routing ◽

Vehicle Routing Problem ◽

Time Windows ◽

Ant Colony ◽

Genetic Operators ◽

Solution Quality ◽

Routing Problem ◽

Soft Time Windows ◽

Heterogeneous Vehicle Routing Problem

Aiming at vehicle routing problem (VRP) with many extended features is widely used in actual life, multi-depot heterogeneous vehicle routing problem with soft time windows (MDHIVRPSTW) mathematical model is established. An improved ant colony optimization (IACO) is proposed for solving this model. Firstly, MDHIVRPSTW was transferred into different groups according to nearest depot method, then constructing the initial route by scanning algorithm (SA). Secondly, genetic operators were introduced, and then adjusting crossover probability and mutation probability adaptively in order to improve the global search ability of the algorithm. Moreover, smooth mechanism was used to improve the performance of ant colony optimization (ACO). Finally, 3-opt strategy was used to improve the local search ability. The proposed IACO has been tested on a 32-customer instance which was generated randomly. The experimental results show that IACO is superior to other three algorithms in terms of convergence speed and solution quality, thus the proposed method is effective and feasible, and the proposed model is better than conventional model.

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