A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
A new optimization algorithm for the vehicle routing problem with time windows
Operations Research
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms applied to the continuous flow shop problem
Computers and Industrial Engineering
Genetic algorithms for flowshop scheduling problems
Computers and Industrial Engineering
Comparing descent heuristics and metaheuristics for the vehicle routing problem
Computers and Operations Research
The vehicle routing problem
Local search with annealing-like restarts to solve the vehicle routing problem with time windows
Proceedings of the 2002 ACM symposium on Applied computing
Multiobjective Scheduling by Genetic Algorithms
Multiobjective Scheduling by Genetic Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Heuristics for Large Constrained Vehicle Routing Problems
Journal of Heuristics
Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics
Journal of Heuristics
A Heuristic for the Vehicle Routing Problem with Time Windows
Journal of Heuristics
Using Constraint-Based Operators to Solve the Vehicle Routing Problem with Time Windows
Journal of Heuristics
Parallelization of a Two-Phase Metaheuristic for Routing Problems with Time Windows
Journal of Heuristics
Genetic Algorithms for the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator
Proceedings of the 3rd International Conference on Genetic Algorithms
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
An Adaptive Clustering Method Using a Geometric Shape for Vehicle Routing Problems with Time Windows
Proceedings of the 6th International Conference on Genetic Algorithms
Timetabling the Classes of an Entire University with an Evolutionary Algorithm
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Hybrid Genetic Algorithm For The Vehicle Routing Problem With Time Windows
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
2-Path Cuts for the Vehicle Routing Problem with Time Windows
Transportation Science
A Branch-and-Cut Procedure for the Vehicle Routing Problem with Time Windows
Transportation Science
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
On the influence of GVR in vehicle routing
Proceedings of the 2003 ACM symposium on Applied computing
A Reactive Variable Neighborhood Search for the Vehicle-Routing Problem with Time Windows
INFORMS Journal on Computing
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Evolutionary Computation
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
A hybrid genetic algorithm for the capacitated vehicle routing problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Parallel simulated annealing for the vehicle routing problem with time windows
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Preferences and their application in evolutionary multiobjectiveoptimization
IEEE Transactions on Evolutionary Computation
Vehicle capacity planning system: a case study on vehicle routing problem with time windows
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Automating the drug scheduling of cancer chemotherapy via evolutionary computation
Artificial Intelligence in Medicine
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Investigating technical trading strategy via an multi-objective evolutionary platform
Expert Systems with Applications: An International Journal
Comparison of similarity measures for the multi-objective vehicle routing problem with time windows
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Preserving population diversity for the multi-objective vehicle routing problem with time windows
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
An evolutionary memetic algorithm for rule extraction
Expert Systems with Applications: An International Journal
An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
Computers and Operations Research
A hybrid algorithm for vehicle routing problem with time windows
Expert Systems with Applications: An International Journal
Optimizing delivery time in multi-objective vehicle routing problems with time windows
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Localized genetic algorithm for vehicle routing problem with time windows
Applied Soft Computing
Journal of Mathematical Modelling and Algorithms
Expert Systems with Applications: An International Journal
A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows
Computers and Industrial Engineering
Bi-Objective Bus Routing: An Application to School Buses in Rural Areas
Transportation Science
An ant colony algorithm for the multi-compartment vehicle routing problem
Applied Soft Computing
Computers and Operations Research
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Vehicle routing problem with time windows (VRPTW) involves the routing of a set of vehicles with limited capacity from a central depot to a set of geographically dispersed customers with known demands and predefined time windows. The problem is solved by optimizing routes for the vehicles so as to meet all given constraints as well as to minimize the objectives of traveling distance and number of vehicles. This paper proposes a hybrid multiobjective evolutionary algorithm (HMOEA) that incorporates various heuristics for local exploitation in the evolutionary search and the concept of Pareto's optimality for solving multiobjective optimization in VRPTW. The proposed HMOEA is featured with specialized genetic operators and variable-length chromosome representation to accommodate the sequence-oriented optimization in VRPTW. Unlike existing VRPTW approaches that often aggregate multiple criteria and constraints into a compromise function, the proposed HMOEA optimizes all routing constraints and objectives simultaneously, which improves the routing solutions in many aspects, such as lower routing cost, wider scattering area and better convergence trace. The HMOEA is applied to solve the benchmark Solomon's 56 VRPTW 100-customer instances, which yields 20 routing solutions better than or competitive as compared to the best solutions published in literature.