The Applications of Metaheuristics in Inventory Routing Problems
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Abstract
Vendor-managed inventory (VMI) is one of the emerging solutions for improving the supply chain efficiency. It gives the vendors the responsibility to monitor and decide the inventory replenishments of their customers. VMI provides a win-win situation for both vendors and customers. The Inventory Routing Problem (IRP) is an important component of VMI policies. In this paper we consider a 1 to many distribution network consisting of a single depot and many geographically dispersed customers where each customer faces demands for a single item which ,arise at a deterministic and customer-specific rate. The problem addressed in this paper is based on a finite horizon, multi-period and single product where a fleet of capacitated vehicles transport items from the depot to meet the demand specified by the customers for each period. We propose a hybrid genetic algorithm based on allocation first, route second method to determine an optimal inventory and transportation policy that minimises the total cost. The computational results for un-split demand have been shown to be superior to those with split demand.
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