Modelos colaborativos para la gestión de inventarios múltiples. Aplicación en el sector artesanal colombiano

El objetivo de esta investigación es generar políticas de gestión de inventarios colaborativas que disminuyan los costos asociados a la gestión de inventarios y aumenten el nivel de servicio ofrecido a los clientes en el sector de las artesanías en Colombia bajo el concepto Vendor Managed Inventory. Planteando un diseño metodológico que consta de cinco fases: revisión de literatura, recopilación de información, análisis de información, formulación y solución de modelos, y generación y simulación de políticas de gestión de inventarios. Obtenido como resultado la formulación de cuatro modelos para realizar la gestión de inventarios: dos modelos estocásticos para una única materia prima y dos modelos estocásticos para múltiples materias primas. Por último, se comparan cada una de las políticas de gestión de inventarios generadas por cada modelo, seleccionando las políticas de gestión de inventarios generadas por los modelos que contemplan múltiples productos, debido a que disminuyen los costos asociados a inventarios y aumentan el nivel de servicio ofrecido a los client

Vendor Managed Inventory: why you need to talk to your supplier

Purpose The purpose of this paper is to investigate the concept of Vendor Managed Inventory (VMI) from an inter-organisational perspective. Extant literature on VMI tends to investigate the concept from a focal perspective, even though VMI has originally been born as a collaborative arrangement. Design/methodology/approach The paper is based on a literature review and an empirical study. It provides a comprehensive literature review on VMI and an illustrative case study of a supplier and a buyer jointly implementing VMI. Findings The findings of this paper are twofold. First, a literature review uncovers that contemporary research has delimited the analysis of VMI to a focal company perspective as current VMI cost models tend not to capture the picture of the complete supply chain. Second, it demonstrates through an illustrative case study that adoption of an inter-organisational approach to VMI is vital if companies are to optimize their buyer-supplier relationships. Research limitations/implications Future research should test the implications proposed in the empirical section, as this piece of research can be seen as exploratory case study research with the aim of analytical generalizations. Practical implications The inter-organisational VMI cost perspective in supply chains should be emphasized in purchasing departments since such a perspective significantly raises the awareness of the costs incurred in a supply chain. Originality/value Existing research has not explicitly focused on inter-organisational costs incurred by companies implementing VMI. This study seeks to bridge this research gapPeer Reviewe

One vendor and multiple retailers system in vendor managed inventory problem with stochastic demand

In many supply networks, the retailers are reluctant to share information about demand and inventory level to the vendor. This might lead to many difficulties for the vendor in establishing his own order/production plan. Vendor managed inventory (VMI) policy can help to solve that problem. By applying VMI, information sharing is not really a problem for the vendor anymore and this policy have been proven to help reduce total inventory cost as well as improve customer service level in the supply network. In this research, a VMI model for the system with one vendor and multiple retailers will be developed. The main target of the model is to determine the retailer’s lot size, the vendor’s lot size, the retailer cycle time, and the number of replenishments in a vendor cycle so as to minimise the total system cost. For solution purpose, simulation-optimisation technique using genetic algorithm is employed to help find optimal solutions for the decision variables. Numerical experiments are conducted to show the applicability of the proposed model. Sensitivity analysis is also conducted to examine the effects of some input parameters on the optimal solution