Bio-Inspired Algorithms for the Vehicle Routing Problem



The vehicle routing problem (VRP) is one of the most famous combinatorial optimization problems. In simple terms, the goal is to determine a set of routes with overall minimum cost that can satisfy several geographical scattered demands. A ?eet of vehicles located in one or more depots is available to ful?ll the requests. A large number of variants exist, adding di?erent constraints to the original de?nition. Some examples are related to the number of depots, the ordering for visiting the customers or to time windows specifying a desirable period to arrive to a given location.
Biological inspired computation is a ?eld devoted to the development of computational tools modeled after principles that exist in natural systems. The adoption of such design principles enables the production of problem solving techniques with enhanced robustness and ?exibility, able to tackle complex optimization situations. Prominent examples of bio-inspired approaches include evolutionary algorithms, swarm intelligence, neural networks or arti?cial immune systems. The ?rst publications reporting the application of bio-inspired approaches to the VRP are from the early 1990’s. Since then, a large number of proposals have been proposed for di?erent variants of the problem. Results presented in recent publications show that bio-inspired approaches are now highly competitive with other state-of-the-art heuristics. Given these circumstances, it is our conviction that this is an excellent occasion for the publication of this book. The fundamental principles related to the application of bio-inspired techniques to the VRP are now well established. In addition, this ?eld of research is extremely active, as it can be con?rmed by an inspection of recent issues of the most important journals and conference proceedings from this area. The goal of the volume is to present a collection of state-of-the-art contributions describing recent developments concerning the application of bio-inspired algorithms to the VRP. Over the 9 chapters, di?erent algorithmic approaches are considered and a diverse set of problem variants are addressed. Some contributions focus on standard benchmarks widely adopted by the research community, while others address real-world situations.


bio-inspired algorithms, vehicle routing


bio-inspired algorithms, vehicle routing

Edited Book

Bio-Inspired Algorithms for the Vehicle Routing Problem, 978-3-540-85151-6, Springer 2009

Cited by

Year 2015 : 3 citations

 A Memetic Differential Evolution Algorithm for the Vehicle Routing Problem with Stochastic Demands
Y Marinakis, M Marinaki, P Spanou - Adaptation and Hybridization in …, 2015 - Springer

 Analytic centre stabilization of column generation algorithm for the capacitated vehicle routing problem
H Karimi, A Seifi - Optimization Methods and Software, 2015 - Taylor & Francis

 Discrete honeybee mating optimization algorithm for the routing of battery-operated automated guidance electric vehicles in personal rapid transit systems
E Fatnassi, O Chebbi, J Chaouachi - Swarm and Evolutionary Computation, 2015 - Elsevier

Year 2012 : 4 citations

 SE Griffis, JE Bell, DJ Closs. Metaheuristics in Logistics and Supply Chain Management.
Journal of Business Logistics, 2012 - Wiley Online Library.

 Y Marinakis. Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing Problem.
Expert Systems with Applications, 2012 - Elsevier

 Edilson Ferneda, Bernardo A. Mello, Janaína D.A.S. Diniz, Adelaide S. Figueiredo. An intelligent vehicle routing system for family farming collective organisations. International Journal of Reasoning-based Intelligent Systems, 2012 - Inderscience.

 Caroline Prodhon. Modèles et méthodes d'optimisationpour des problèmes di ciles de localisationet tournées de véhicules. Habilitation à diriger des recherches. Université de Technologie de Compiegne, 2012.

Year 2010 : 4 citations

 Y Marinakis, M Marinaki. A hybrid genetic–Particle Swarm Optimization Algorithm for the vehicle routing problem. Expert Systems with Applications, 2010 - Elsevier

 Y Marinakis, M Marinaki. Bumble Bees Mating Optimization Algorithm for the Vehicle Routing Problem. Handbook of Swarm Intelligence, 2010 - Springer

 E Ferneda, B Mello, J Diniz, A Figueiredo. Reasoning elements for a vehicle routing system. Knowledge-Based and Intelligent Information and Engineering Systems, LNCS, 2010 - Springer

 A Garcia Najera. Multi-Objective evolutionary algorithms for vehicle routing problems. PhD Thesis, 2010

Year 2009 : 1 citations

 T Weise, A Podlich, C Gorldt . Solving real-world vehicle routing problems with evolutionary algorithms. Natural Intelligence for Scheduling, Planning and Packing Problems, Studies in Computational Intelligence, 2009 - Springer