A tabu search heuristic for the vehicle routing problem
Management Science
The vehicle routing problem
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Parallel Approaches for Multiobjective Optimization
Multiobjective Optimization
The Consistent Vehicle Routing Problem
Manufacturing & Service Operations Management
A population-based local search for solving a bi-objective vehicle routing problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
On the interactive resolution of multi-objective vehicle routing problems
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
Computers and Operations Research
A bi-objective vehicle routing problem with time windows: A real case in Tenerife
Applied Soft Computing
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In this paper, we address a bi-objective vehicle routing problem in which the total length of routes is minimized as well as the balance of routes, i.e. the difference between the maximal route length and the minimal route length. For this problem, we propose an implementation of the standard multi-objective evolutionary algorithm NSGA II. To improve its efficiency, two mechanisms have been added. First, a parallelization of NSGA II by means of an island model is proposed. Second, an elitist diversification mechanism is adapted to be used with NSGA II. Our method is tested on standard benchmarks for the vehicle routing problem. The contribution of the introduced mechanisms is evaluated by different performance metrics. All the experimentations indicate a strict improvement of the generated Pareto set.