Bio-inspired Algorithms for the Vehicle Routing Problem

1. Front Matter

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2. A Review of Bio-inspired Algorithms for Vehicle Routing

   • Jean-Yves Potvin

   Pages 1-34

3. A GRASP × Evolutionary Local Search Hybrid for the Vehicle Routing Problem

   • Christian Prins

   Pages 35-53

4. An Evolutionary Algorithm for the Open Vehicle Routing Problem with Time Windows

   • Panagiotis P. Repoussis, Christos D. Tarantilis, George Ioannou

   Pages 55-75

5. Using Genetic Algorithms for Multi-depot Vehicle Routing

   • Beatrice Ombuki-Berman, Franklin T. Hanshar

   Pages 77-99

6. Hybridizing Problem-Specific Operators with Meta-heuristics for Solving the Multi-objective Vehicle Routing Problem with Stochastic Demand

   • Chun Yew Cheong, Kay Chen Tan

   Pages 101-129

7. Exploiting Fruitful Regions in Dynamic Routing Using Evolutionary Computation

   • J. I. van Hemert, J. A. La Poutré

   Pages 131-149

8. EVITA: An Integral Evolutionary Methodology for the Inventory and Transportation Problem

   • Anna I. Esparcia-Alcázar, Manuel Cardós, J. J. Merelo, Anaís Martínez-García, Pablo García-Sánchez, Eva Alfaro-Cid et al.

   Pages 151-172

9. A Memetic Algorithm for a Pick-Up and Delivery Problem by Helicopter

   • Nubia Velasco, Philippe Castagliola, Pierre Dejax, Christelle Guéret, Christian Prins

   Pages 173-190

10. When the Rubber Meets the Road: Bio-inspired Field Service Scheduling in the Real World

    • Israel Beniaminy, Dovi Yellin, Uzi Zahavi, Marko Žerdin

    Pages 191-213

11. Back Matter

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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 - mands. 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. The original version of this problem was proposed by Dantzig and Ramser in 1959 [1]. In their seminal paper, the authors address the calculation of a set of optimal routes for a ?eet of gasoline delivery trucks. Since then, the VRP has attractedtheattentionofalargenumberofresearchers.Aconsiderablepartofits success is a consequence of its practical interest, as it resembles many real-world problems faced everyday by distribution and transportation companies, just to mention a few applications areas. In this context, the development of e?cient optimization techniques is crucial. They are able to provide new and enhanced solutionstologisticoperations,andmaythereforeleadtoasubstantialreduction in costs for companies. Additionally, and from a research oriented perspective, the VRP is a challenging NP-hard problem providing excellent benchmarks to access the e?ciency of new global optimization algorithms.

• GRASP
• algorithm
• algorithms
• bio-inspired algorithm
• combinatorial optimization
• design
• development
• evolutionary algorithm
• evolutionary computation
• genetic algorithms
• heuristics
• metaheuristic
• optimization
• problem solving
• scheduling

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