A stochastic multiitem replenishment and delivery problem with leadtime reduction initiatives and the solving methodologies Abstract   With the intensification of timebased competition, the importance of reducing leadtime by rapidly delivering multiorders has been underscored in the process of replenishmentstoragetransportation. This perception has prompted enterprises to increase expenditure on purchasing modern timetracing technologies (e.g. RFID), and equipping facilities for item fast movement (e.g. highrack automatic shelves) to retain customers. In this study, we explore a novel extension of the multiitem joint replenishment problem (JRP) with leadtime compressing initiatives. By assuming controllable leadtime, we construct a stochastic periodicreview joint replenishment and delivery (JRD) model to investigate impacts of capital investment in leadtime reduction to the decisions of multiitem joint replenishment and delivery. To solve the proposed JRD, two heuristics and a differential evolutionary algorithm are presented based on the model property analyses. The experimental results reveal the performance differences (e.g., searching speed, robustness and searching effectiveness) of three algorithms. Furthermore, our findings have managerial implications that proper investment in leadtime reduction not only helps shorten replenishment time and cut major ordering cost, but can also reduce the system cost.

Robust Inventory Routing Problem with Replenishment Lead Time The inventory routing problem (IRP) is studying how to deliver products to several customers from the supplier, which is a combination of inventory management and vehicle routing problems. This paper studied an IRP with considering the time consumption in transportation, which is the replenishment lead time. In this problem, the delivery sequence impacts the transport cost and the replenishment lead time of customers. Three decisions should be made: 1) which customer should be replenished; 2) how much goods should be delivered; 3) the delivery sequence. In this paper, we proposed a single period model, which can very easily be extended to a rolling horizon policy for solving the infinity horizon IRP. We discussed the closedform solution of robust inventory policy and proposed a Genetic Algorithm to solve this problem. Finally, a numerical example is provided to indicate the feasibility of the algorithm.