Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
The vehicle routing problem
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics
Journal of Heuristics
Using Constraint-Based Operators to Solve the Vehicle Routing Problem with Time Windows
Journal of Heuristics
A Diversity-Controlling Adaptive Genetic Algorithm for the Vehicle Routing Problem with Time Windows
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Procedural texture evolution using multi-objective optimization
New Generation Computing
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Evolutionary Computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Dynamic vehicle routing using genetic algorithms
Applied Intelligence
Multi-objective UAV mission planning using evolutionary computation
Proceedings of the 40th Conference on Winter Simulation
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
The Vehicle Routing Problem with Real-Time Travel Times
Proceedings of the 2008 conference on Techniques and Applications for Mobile Commerce: Proceedings of TAMoCo 2008
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
A search space analysis for the waste collection 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
Mathematical study of trade-off relations in logistics systems
Journal of Computational and Applied Mathematics
Arc-guided evolutionary algorithm for the vehicle routing problem with time windows
IEEE Transactions on Evolutionary Computation
Waste collection vehicle routing problem with time windows using multi-objective genetic algorithms
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
A multiagent architecture for solving combinatorial optimization problems through metaheuristics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A genetic algorithm to logistics distribution vehicle routing problem with fuzzy due time
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Computers and Operations Research
An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
Computers and Operations Research
A case-based classifier for hypertension detection
Knowledge-Based Systems
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
Planning and optimising organisational travel plans using an evolutionary algorithm
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume 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
Incorporating emissions models within a multi-objectivevehicle routing problem
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Using graphical information systems to improve vehicle routing problem instances
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm
Expert Systems with Applications: An International Journal
Cooperative particle swarm optimization for multiobjective transportation planning
Applied Intelligence
Task scheduling and motion planning for an industrial manipulator
Robotics and Computer-Integrated Manufacturing
The impact of food perishability issues in the vehicle routing problem
Computers and Industrial Engineering
An ant colony algorithm for the multi-compartment vehicle routing problem
Applied Soft Computing
Computers and Operations Research
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The Vehicle Routing Problem with Time windows (VRPTW) is an extension of the capacity constrained Vehicle Routing Problem (VRP). The VRPTW is NP-Complete and instances with 100 customers or more are very hard to solve optimally. We represent the VRPTW as a multi-objective problem and present a genetic algorithm solution using the Pareto ranking technique. We use a direct interpretation of the VRPTW as a multi-objective problem, in which the two objective dimensions are number of vehicles and total cost (distance). An advantage of this approach is that it is unnecessary to derive weights for a weighted sum scoring formula. This prevents the introduction of solution bias towards either of the problem dimensions. We argue that the VRPTW is most naturally viewed as a multi-objective problem, in which both vehicles and cost are of equal value, depending on the needs of the user. A result of our research is that the multi-objective optimization genetic algorithm returns a set of solutions that fairly consider both of these dimensions. Our approach is quite effective, as it provides solutions competitive with the best known in the literature, as well as new solutions that are not biased toward the number of vehicles. A set of well-known benchmark data are used to compare the effectiveness of the proposed method for solving the VRPTW.