Manufacturers, who re-supply a large number of customers, continually struggle with the
question of how to formulate a replenishment strategy. The purpose of this paper is to determine the
optimal set of routes for a group of vehicles in the transportation network under defined constraints –
which is known as the Vehicle Routing Problem (VRP) – delivering new items, and resolving the
inventory control decision problem simultaneously since the regular VRP does not. Both the vehicle
routing decision for delivery and the inventory control decision affect each other and must be
considered together. Hence, a mathematical model of vehicle routing problem with inventory is
proposed whose demands are assumed to be hybrid variables (HVRPI) in which fuzziness and
randomness are considered together. Then, the problem is transformed into its equivalent deterministic
form and presented as a multi-objective mixed integer nonlinear programming. Since finding the
optimal solution(s) for HVRPI is a NP-hard, a solution algorithm is presented composed of the
constrained Nelder–Mead method and a Tabu search algorithm for the vehicle routing to solve the
complex problem. The usefulness of the model is validated by experimental results. The findings
indicate that the proposed model can provide a practical tool to significantly reduce the logistic cost.
Keywords Vehicle Routing Problem, Hybrid Variable, Nelder–Mead Method, Tabu Search.
Malekly A. A Vehicle Routing Problem with Inventory in a Hybrid Uncertain Environment. International Journal of Applied Operational Research 2012; 2 (1) URL: http://ijorlu.liau.ac.ir/article-1-105-en.html