A Quantum Particle Swarm-Inspired Algorithm for Dynamic Vehicle Routing Problem

2017 ◽  
pp. 185-190
Author(s):  
Bo Li ◽  
Guo Chen ◽  
Ning Tao
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

scholarly journals Multiobjective Dynamic Vehicle Routing Problem and Time Seed Based Solution Using Particle Swarm Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Omprakash Kaiwartya ◽  
Sushil Kumar ◽  
D. K. Lobiyal ◽  
Pawan Kumar Tiwari ◽  
Abdul Hanan Abdullah ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Particle Swarm ◽  
New Delhi ◽  
Satisfaction Level ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Swarm Optimization ◽  
Routing Problem

A multiobjective dynamic vehicle routing problem (M-DVRP) has been identified and a time seed based solution using particle swarm optimization (TS-PSO) for M-DVRP has been proposed. M-DVRP considers five objectives, namely, geographical ranking of the request, customer ranking, service time, expected reachability time, and satisfaction level of the customers. The multiobjective function of M-DVRP has four components, namely, number of vehicles, expected reachability time, and profit and satisfaction level. Three constraints of the objective function are vehicle, capacity, and reachability. In TS-PSO, first of all, the problem is partitioned into smaller size DVRPs. Secondly, the time horizon of each smaller size DVRP is divided into time seeds and the problem is solved in each time seed using particle swarm optimization. The proposed solution has been simulated in ns-2 considering real road network of New Delhi, India, and results are compared with those obtained from genetic algorithm (GA) simulations. The comparison confirms that TS-PSO optimizes the multiobjective function of the identified problem better than what is offered by GA solution.

scholarly journals A Modified Harmony Search Algorithm for Solving the Dynamic Vehicle Routing Problem with Time Windows

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shifeng Chen ◽  
Rong Chen ◽  
Jian Gao
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.

A multi-objective dynamic vehicle routing problem with fuzzy time windows: Model, solution and application

2014 ◽  
Vol 14 ◽  
pp. 504-527 ◽  
Author(s):  
Seyed Farid Ghannadpour ◽  
Simak Noori ◽  
Reza Tavakkoli-Moghaddam ◽  
Keivan Ghoseiri
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Model Solution ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem ◽  
Multi Objective
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