Simulation Study Of Cement Distribution Considering Stock Criticality And Shipment Due-Date

The expansion of Indonesia’s infrastructure will effect to the increasing of cement sales. It is very optimistic that cement demand in Indonesia will rise significantly. PT.X is one of the leading cement producer in Indonesia which has two methods of delivery, sea transportation and land transportation using trucks. The utilization of land transportation of PT.X is more dominant than the sea transportation. Thus, the optimization for land transportation in PT.X is highly recommended due to its high frequency. One of the problem in PT.X is the market of PT.X often run out of stock condition while there are plenty of stock in the plant. the current condition is the distribution order will be directly released after the order is received by the plant and delivered based on the earliest estimated due date of the delivery request. Moreover, there are no visibility of information between the plant and the distributor and the availability of the truck cannot be predicted due to the uncertainty of cycle time. This research aim to optimize the distribution of the cement using Vendor Managed Inventory (VMI) model which consider the visibility of information between plant and distributor. The method in this research is conducting a simulation study which considers the stock criticality of each distributor as the trigger of releasing the order. By considering the stock criticality of each market will increase the product availability, increase the percentage of on-time delivery, and maintain the utilization of the truck. By using the same dispatching rule with additional number of the truck, the simulation process results in higher fill rate, lower truck utilization, and higher rate of on-time delivery. The suggested scenario is scenario 7 with fill rate 81.3%, truck utilization 31.6%, and on-time delivery 32.5%. Scenario 7 utilizes 300 trucks and implement stock criticality method

Vendor Managed inventory, from concept to processes, for an unified view

International audienceIn a supplier-customer relationship, Vendor Managed Inventory (VMI) is currently used to monitor the customer's inventory replenishment. However the integration of VMI implies consequences on the collaboration process that links the different planning processes of each partner. This paper proposes a unified view of the VMI: beyond the short term pull system inventory replenishment, partners have to share their vision of the demand, their requirements and their constraints to fix middle/long term common objectives for each article concerned by VMI. There are many ways to specify these links between VMI and partner's planning processes

Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model

The classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. In this paper, a new policy entitled “Allocation-In-Fraction-Out (AIFO)” is proposed. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Consequently, three general two-warehouse inventory models for items that are subject to inspection for imperfect quality are developed and compared – each underlying one of the dispatching policies considered. Each sub-replenishment that is delivered to OW and RW incurs a distinct transportation cost and undertakes a 100 per cent screening. The mathematical formulation reflects a diverse range of time-varying forms. The paper provides illustrative examples that analyse the behaviour of deterioration, value of information and perishability in different settings. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning, but may also suggest outsourcing the inventory holding through vendor managed inventory

On the inventory routing problem with stationary stochastic demand rate

One of the most significant paradigm shifts of present business management is that individual businesses no longer participate as solely independent entities, but rather as supply chains (Lambert and Cooper, 2000). Therefore, the management of multiple relationships across the supply chain such as flow of materials, information, and finances is being referred to as supply chain management (SCM). SCM involves coordinating and integrating these multiple relationships within and among companies, so that it can improve the global performance of the supply chain. In this dissertation, we discuss the issue of integrating the two processes in the supply chain related, respectively, to inventory management and routing policies. The challenging problem of coordinating the inventory management and transportation planning decisions in the same time, is known as the inventory routing problem (IRP). The IRP is one of the challenging optimization problems in logis-tics and supply chain management. It aims at optimally integrating inventory control and vehicle routing operations in a supply network. In general, IRP arises as an underlying optimization problem in situations involving simultaneous optimization of inventory and distribution decisions. Its main goal is to determine an optimal distribution policy, consisting of a set of vehicle routes, delivery quantities and delivery times that minimizes the total inventory holding and transportation costs. This is a typical logistical optimization problem that arises in supply chains implementing a vendor managed inventory (VMI) policy. VMI is an agreement between a supplier and his regular retailers according to which retailers agree to the alternative that the supplier decides the timing and size of the deliveries. This agreement grants the supplier the full authority to manage inventories at his retailers'. This allows the supplier to act proactively and take responsibility for the inventory management of his regular retailers, instead of reacting to the orders placed by these retailers. In practice, implementing policies such as VMI has proven to considerably improve the overall performance of the supply network, see for example Lee and Seungjin (2008), Andersson et al. (2010) and Coelho et al. (2014). This dissertation focuses mainly on the single-warehouse, multiple-retailer (SWMR) system, in which a supplier serves a set of retailers from a single warehouse. In the first situation, we assume that all retailers face a deterministic, constant demand rate and in the second condition, we assume that all retailers consume the product at a stochastic stationary rate. The primary objective is to decide when and how many units to be delivered from the supplier to the warehouse and from the warehouse to retailers so as to minimize total transportation and inventory holding costs over the finite horizon without any shortages

A tabu search-based heuristic for the dynamic oil distribution problem

Ce mémoire traite l'intégration dynamique des opérations de gestion des stocks et du transport avec la présence d'un évènement perturbateur, qui est la livraison urgente sur appel imprévue. En s'inspirant du cadre général de l'industrie énergétique et la distribution de l'huile à chauffage en particulier, après une revue de littérature exhaustive des problèmes de tournées de véhicules dynamiques et stockage-routage, nous introduisons une nouvelle variante qui cadre le problème dynamique de stockage-routage avec livraisons sur appel. Notre démarche de traitement s'est devisée en deux grandes étapes. Une première étape, statique et déterministe, s'est focalisée sur la description et la formulation mathématique du problème en se basant sur la programmation linéaire mixte et une résolution exacte à travers l'algorithme de branch-and-cut. Pour le besoin de l'intégration dynamique des livraisons incertaines sur appel dans un temps d'exécution raisonnable, une deuxième étape dynamique s'est concentrée sur le développement d'une heuristique basée sur la recherche tabou avec la configuration de deux politiques dynamiques de contrôle qui étudient les possibilités d'insérer les visites dynamiques soit dans la route en cours d'exécution ou dans celle de la période suivante dans le cas échéant. 72 instances ont été générées, et des analyses ont été menées sur différents facteurs qui peuvent influencer le taux de service des clients dynamiques aussi que les coûts d'opération.This thesis deals with the dynamic integration of inventory management and transportation operations with the uncertain event of unplanned deliveries following urgent calls. Inspired by the general framework of the energy industry and the distribution of heating oil, in particular, a comprehensive literature review of both problems of dynamic vehicle routing and inventory-routing are conducted. We then introduce a new variant, called the dynamic inventory-routing problem with customer requests. Our solution approach has been divided into two main steps. A static and deterministic first step focused on the mathematical description and formulation of the problem based on a mixed-integer programming model and the development of an exact solution approach through a branch and cut algorithm. Then, to dynamically integrate uncertain on-call deliveries in a reasonable execution time, a second dynamic step is established to develop a heuristic, based on tabu search, with the configuration of two dynamic control policies that consider the possibilities of inserting dynamic visits either in the route under the execution or in that of the following period. 72 instances are generated, and analyses are conducted on various factors that can influence the service level for dynamic customers and operation costs

An analysis on vendor hub

Master'sMASTER OF SCIENCE (MANAGEMENT

The integrated deterministic model for a vendor manage inventory in a two-stage supply chain

In a two-stage supply chain system, vendor managed inventory (VMI) policies is an integrating decisions between a supplier and his retailers.The supplier assumes the responsibility of maintaining inventory at its retailers and ensuring that they will not run out of stock at any moment.This paper discusses an optimization approach, considering the model of static demand on the inbound as well as the outbound inventory for a two-stage supply chain implementing VMI. In the proposed solutions for coordinating the single warehouse multiple-retailers (SWMR) system, retailers are first clustered to minimize the within-cluster travel costs and distances and are then replenished using an optimal direct shipping strategy satisfying some additional restriction

Nestle Thailand's Best Practice, a Support Idea on Support Best Practice VMI: An Enable of Conceptual Collaboration

This paper purposed to present collaboration support a best practice through the implementation for Vendor Manage Inventory (VMI). The desire to get rid of the non-valueadded costs associated with trading partners’ relationship and explore basic issues of Nestlé’s Thailand related to her best practice mission as a case study. One of key is related to VMI implementation, including its benefits/pitfalls and higher service level. The empirical data were collected through site visit with an interview and discussion with sophomore practitioners. This studying, Nestlé’s VMI implementation explained into illustration. Findings, VMI technologies as information systems can develop collaboration among the partners. The organization was under win/win concept, increment of partners’ relationship and reduction of sales lost, bullwhip, with evolution of ordering system. Findings of this study showed all the features of VMI influenced value in service level improvement significantly. The best practice approaches were explored. This paper conclusion values for academic’s learning and practitioner’s knowledge. The scope of study only within range of VMI practiced as a single tool in best practice concept. Practical implications, this paper confirms the power of VMI - a collaboration concept is most concerned factor, especially "trust" among partner with benefits for costs and waste reduction. The paper discussed implementation challenges, identifies adoption phases and reviews VMI key success factors. Results identified the biggest challenge as not for IT experts in determining how to integrate VMI with existing partners, recapitalized or investment but customer relationship (trust) and the volume of purchasing are the main factors of the difficulty in VMI implementation to enhance the company's best practice