Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Solving real-life vehicle routing problems efficiently using tabu search
Annals of Operations Research - Special issue on Tabu search
A tabu search heuristic for the multi-depot vehicle routing problem
Computers and Operations Research
A tabu search heuristic for the heterogenous fleet vehicle routing problem
Computers and Operations Research
SavingsAnts for the Vehicle Routing Problem
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
A Savings Based Ant System For The Vehicle Routing Problem
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Improving public transit access to in-city villages
International Journal of Data Analysis Techniques and Strategies
An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup
Computers and Operations Research
Survey: The vehicle routing problem: A taxonomic review
Computers and Industrial Engineering
International Journal of Data Analysis Techniques and Strategies
Ant colony search algorithms for optimal packing problem
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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Routing of service vehicles are the heart of many service operations. Exclusively vehicle routing problem VRP plays a central role in the optimization of distribution networks. The routing of service vehicles has a major impact on the quality of the service provided. In distribution of goods and services, it is time and again required to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most commonly studied is where all vehicles are identical. Due to the complexity involved in solving the VRP, most researchers concentrate on using meta-heuristics for solving real-life problems. In this paper, heuristic methods based on Ant Colony Optimization and Simulated Annealing algorithms are developed and search strategies are investigated. Computational results are reported on randomly generated problems. These methods significantly improve in minimizing the total distances travelled by the vehicles.