A tabu search heuristic for the vehicle routing problem
Management Science
The vehicle routing problem
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
A cooperative parallel meta-heuristic for the vehicle routing problem with time windows
Computers and Operations Research
Lagrangian duality applied to the vehicle routing problem with time windows
Computers and Operations Research
Vehicle routing problem with elementary shortest path based column generation
Computers and Operations Research
A general heuristic for vehicle routing problems
Computers and Operations Research
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
The Shortest-Path Problem with Resource Constraints and k-Cycle Elimination for k ≥ 3
INFORMS Journal on Computing
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Transportation Science
Discrete Applied Mathematics
Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows
Operations Research
Edge assembly crossover for the capacitated vehicle routing problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Efficient local search limitation strategies for vehicle routing problems
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
New EAX crossover for large TSP instances
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Fast EAX algorithm considering population diversity for traveling salesman problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
A powerful route minimization heuristic for the vehicle routing problem with time windows
Operations Research Letters
Multidimentional self-organization for online time-constrained vehicle routing problems
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part II
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Solving variants of the vehicle routing problem with a simple parallel iterated Tabu search
INOC'11 Proceedings of the 5th international conference on Network optimization
A parallel iterated tabu search heuristic for vehicle routing problems
Computers and Operations Research
Journal of Mathematical Modelling and Algorithms
Fleet organization models for online vehicle routing problems
Transactions on Computational Collective Intelligence VII
Computers and Operations Research
Expert Systems with Applications: An International Journal
Support vector machines training data selection using a genetic algorithm
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows
Computers and Industrial Engineering
Adaptive Path Relinking for Vehicle Routing and Scheduling Problems with Product Returns
Transportation Science
Computers and Operations Research
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In this paper, we present an effective memetic algorithm for the vehicle routing problem with time windows (VRPTW). The paper builds upon an existing edge assembly crossover (EAX) developed for the capacitated VRP. The adjustments of the EAX operator and the introduction of a novel penalty function to eliminate violations of the time window constraint as well as the capacity constraint from offspring solutions generated by the EAX operator have proven essential to the heuristic's performance. Experimental results on Solomon's and Gehring and Homberger benchmarks demonstrate that our algorithm outperforms previous approaches and is able to improve 184 best-known solutions out of 356 instances.