Transportation Costs and Carbon Emissions in a Vendor Managed Inventory Situation

A novel green delivery method for express delivery based on the urban metro network, referred to as Green metro express delivery (GMED), is presented. A multi-objective mathematical programming model is first proposed to maximize the search for the best transportation costs and lowest carbon emissions. To solve the GMED model e-ciently, a two-layer coding method is used to encode the path and the non-dominated sorting genetic algorithm II (NSGA-II) is adopted. Finally, a numerical experiment was conducted with Ningbo Metro Network as a case to prove the effectiveness and stability of NSGA-II in solving the GMED model. The result shows that: (a) Compared with the vehicle express delivery method (VED), GMED has lower carbon emissions and vehicle mileage. (b) For the same quantity of express delivery, the transportation costs of GMED and VED have their own advantages over different transportation distances. (c) For delivery distances with the same transportation cost, the lager the quantity of express delivery, the lower the transportation cost of GMED compared to VED.

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New Formulation for an Economic Order Quantity Distribution Policy in Vendor-Managed Inventory Routing Problems

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.945-949.3219 ◽

2014 ◽

Vol 945-949 ◽

pp. 3219-3236 ◽

Cited By ~ 1

Author(s):

Thiago Guimarães ◽

Cassius Tadeu Scarpin ◽

Maria Teresinha Arns Steiner

Keyword(s):

Planning Horizon ◽

Transportation Costs ◽

Economic Order Quantity ◽

Economic Order ◽

Inventory Routing ◽

Order Quantity ◽

Vendor Managed Inventory ◽

Routing Problem ◽

Inventory Routing Problem ◽

New Formulation

In vendor managed inventory systems, logistics decisions are centralized at the vendor, allowing inventory storage and transportation costs to be reduced simultaneously. Operation of such systems requires the solution of a complex combinatorial optimization problem, known as the Inventory Routing Problem (IRP), which involves managing client inventory and determining the frequency and size of product deliveries as well as the route taken by the vehicle over a given planning horizon. We present a new formulation based on an economic order quantity distribution policy for the multivehicle inventory routing problem (MIRP). A mathematical programming model with additional practical constraints was used for the MIRP. A new heuristic approach that breaks the MIRP down into the following two sub-problems was also proposed: one dealing with the scheduling of deliveries and the formation of delivery clusters over the planning horizon, and the second sub-problem, which builds the routes for the delivery clusters using classic route construction heuristics and a procedure for intra-route improvements. Adjustments between routes are performed with the aid of a new large neighborhood search (LNS) strategy. Small, medium-sized and large scenarios with different storage and transportation costs were generated using parameters based on data from the literature. Extensive computational tests were carried out to determine the effectiveness of the proposed distribution policy and the heuristic used.

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