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Model and Heuristics for the Heterogeneous Fixed Fleet Vehicle Routing Problem with Pick-Up and Delivery

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Purpose – This paper discusses the heterogeneous fixed fleet vehicle routing problem with pick-up and delivery (HFFVRPPD), for vehicles with different capacities, fixed costs, and travel costs. Research Design, data, methodology – This paper made nine assumptions for establishing a mathematical model to describe HFFVRPPD. It established a practical mathematical model, and because of the non-deterministic polynomial-time hard (NP-hard), improved the traditional simulated annealing algorithm and tested a new algorithm using a certain scale model. Result – We calculated the minimum cost of the heterogeneous fixed fleet vehicle routing problem (HFFVRP) with a single task and, on comparing the results with the actual HFFVRP for the single task alone, observed that the total cost of HFFVRPPD reduced significantly by 46.7%. The results showed that the new algorithm provides better solutions and stability. Conclusions – This paper, by comparing the HFFVRP and HFFVRPPD results, highlights certain advantages of using HFFVRPPD in physical distribution enterprises, such as saving distribution vehicles, reducing logistics cost, and raising economic benefits.

Abstract

Purpose – This paper discusses the heterogeneous fixed fleet vehicle routing problem with pick-up and delivery (HFFVRPPD), for vehicles with different capacities, fixed costs, and travel costs. Research Design, data, methodology – This paper made nine assumptions for establishing a mathematical model to describe HFFVRPPD. It established a practical mathematical model, and because of the non-deterministic polynomial-time hard (NP-hard), improved the traditional simulated annealing algorithm and tested a new algorithm using a certain scale model. Result – We calculated the minimum cost of the heterogeneous fixed fleet vehicle routing problem (HFFVRP) with a single task and, on comparing the results with the actual HFFVRP for the single task alone, observed that the total cost of HFFVRPPD reduced significantly by 46.7%. The results showed that the new algorithm provides better solutions and stability. Conclusions – This paper, by comparing the HFFVRP and HFFVRPPD results, highlights certain advantages of using HFFVRPPD in physical distribution enterprises, such as saving distribution vehicles, reducing logistics cost, and raising economic benefits.

참고문헌 (9)

  1. Angelelli, E., "The Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery", Distribution Logistics and Supply Chain Management, 30(6), pp.249~267 (2002)
  2. Anily, S., "The Vehicle Routing Problems with Delivery and Back-haul Options", Naval Research Logistics, 17(43), pp.415~434 (1996)
  3. Baldacci, R., "Routing a heterogeneous fleet of vehicles", Journal of Transportation Systems Engineering and Information Technology, 12(2), pp.23~27 (2007)
  4. Dantzig, G., "The Truck Dispatching Problem", Management Science, 6(1), pp.80~91 (1959)
  5. Doris, S., "Hybrid adaptive predictive control for the multi-vehicle dynamic pick-up and delivery problem based on genetic algorithms and fuzzy clustering", Computers & Operations Research, 16(35), pp.3412~3438 (2008)
  6. Lin, Shih-Wei, "Solving the truck and trailer routing problem based on a simulatedannealing heuristic", Computers & OperationsResearch, 36(5), pp.1683~1692 (2009)
  7. Liu, Yun-zhong, "Summarizing Research on Models and Algorithms for Vehicle Routing Problem", Journal of Industrial Engineering, 2005, pp.19(1), 124~130
  8. Taillard, E., "A heuristic column generation method for the heterogeneous fleet VRP", Ramiro Research Operation, 33(1), pp.114~ (1999)
  9. Toth, P., "An overview of vehicle routing problems", Society for Industrial and Applied Mathematics, 36(10), pp.183~192 (2001)

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