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• W2527823986 abstract "The need for efficient transportation is ever increasing in every society over the globe. Transportation costs account for a significant percentage of the total cost of a product. Strong global competition continues to aggravate the demand for higher efficiency, high quality of service, timeliness, reactivity, and cost-effectiveness in transportation. It is therefore important to optimize vehicle routing in order to provide cost-effective services to customers and to maintain the momentum of the business in the long term. Multiple criteria such as routing cost and workload balancing should be considered. This chapter considers the fleet size and mix vehicle routing problem (FSMVRP), where the fleet size and its composition are to be determined. A multi-criterion grouping genetic algorithm (GGA) with unique grouping genetic operators is presented and tested on benchmark problems. Comparative computational results show that GGA is competitive in multi-criterion decision making." @default.
• W2527823986 created "2016-10-14" @default.
• W2527823986 creator A5051314849 @default.
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• W2527823986 date "2016-10-05" @default.
• W2527823986 modified "2023-09-27" @default.
• W2527823986 title "Fleet Size and Mix Vehicle Routing: A Multi-Criterion Grouping Genetic Algorithm Approach" @default.
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• W2527823986 doi "https://doi.org/10.1007/978-3-319-44394-2_8" @default.
• W2527823986 hasPublicationYear "2016" @default.
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