Drop-Shipping at a Promotional Products Distributor

During the current economic times, companies are trying to reduce costs by incorporating new strategies into their business plan. Supply chain, in particular the distribution network is one area where an improvement can bring in a healthy return on investment to a company. Drop-shipping is a distribution strategy whereby customer orders are fulfilled by directly delivering products from manufacturer\u27s facility, instead of storing these products at the warehouse. Drop-shipping helps in reducing inventory and material handling costs at the warehouse, but may increase transportation costs due to frequent shipments. This research was motivated by the current operations at a promotional products distributor in the Midwest US. This distributor wanted to decide which products to drop-ship versus stock in the warehouse. We develop a mixed integer programming (MIP) model to categorize the products as \u27to be drop-shipped\u27 or \u27kept in warehouse\u27 with the objective of minimizing the total distribution cost. This single-period MIP model assumes deterministic demand, all-unit transportation LTL and parcel rates, and warehouse space. To solve larger problem instances, a Ruin and Recreate (RR) based heuristic is proposed. Numerical results indicate that a savings in warehouse space ranging between 28-53% and an additional cost savings of up to 5.2%. A case study involving realistic data obtained from the distributor is presented and avenues for future research in this area are discussed

Hybrid Heuristics for Infinite Period Inventory Routing Problem

In this paper, we address a one-to-many distribution network inventory routing problem over an infinite planning horizon. Each retailer has an independent, random demand, and the distribution center uses capacitated vehicles for routing delivery. The demand at each retailer is relatively small compared to the vehicle capacity. A novel mathematical model is given to simultaneously decide the optimal routing tours to retailers and routing frequencies of each route. Several heuristics are developed to solve large scale instances of the problem

Analysing the effectiveness of vendor-managed inventory in a single-warehouse, multiple-retailer system

This paper considers a two-stage supply chain, consisting of a single warehouse and multiple retailers facing deterministic demands, under a vendor-managed inventory (VMI) policy.It presents a two-phase optimisation approach for coordinating the shipments in this VMI system.The first phase uses direct shipping from the supplier to all retailers to minimise the overall inventory costs.Then, in the second phase, the retailers are clustered using a construction heuristic in order to optimise the transportation costs while satisfying some additional restrictions.The improvement of the system's performance through coordinated VMI replenishments against the system with direct shipping only is shown and discussed in the comparative analysis section

Optimization of the fuel chips production and distribution network with Forest and Landscape, Denmark

SC

Integrated Supply Chain Network Design: Location, Transportation, Routing and Inventory Decisions

abstract: In this dissertation, an innovative framework for designing a multi-product integrated supply chain network is proposed. Multiple products are shipped from production facilities to retailers through a network of Distribution Centers (DCs). Each retailer has an independent, random demand for multiple products. The particular problem considered in this study also involves mixed-product transshipments between DCs with multiple truck size selection and routing delivery to retailers. Optimally solving such an integrated problem is in general not easy due to its combinatorial nature, especially when transshipments and routing are involved. In order to find out a good solution effectively, a two-phase solution methodology is derived: Phase I solves an integer programming model which includes all the constraints in the original model except that the routings are simplified to direct shipments by using estimated routing cost parameters. Then Phase II model solves the lower level inventory routing problem for each opened DC and its assigned retailers. The accuracy of the estimated routing cost and the effectiveness of the two-phase solution methodology are evaluated, the computational performance is found to be promising. The problem is able to be heuristically solved within a reasonable time frame for a broad range of problem sizes (one hour for the instance of 200 retailers). In addition, a model is generated for a similar network design problem considering direct shipment and consolidation within the same product set opportunities. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.Dissertation/ThesisPh.D. Industrial Engineering 201

Abordagem determinística e estocástica na formulação de políticas de distribuição por lote econômico de entrega, em problemas de roteirização com estoque gerenciado pelo fornecedor e sistema logístico em três níveis

Orientadora : Profª Dra. Maria Teresinha Arns SteinerCo-orientador : Prof. Dr. Cassius Tadeu ScarpinTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 29/09/2015Inclui referências : f. 261-275Área de concentração : Programação matemáticaResumo: Em sistemas de gerenciamento de estoque pelo fornecedor (Vendor Managed Inventory - VMI), as decisões logísticas são centralizadas ao nível do vendedor, possibilitando uma redução simultânea dos custos de armazenagem e transporte. A operação de sistemas VMI requer a resolução de um complexo problema de otimização combinatória, denominado Problema de Roteirização e Estoques (PRE). O PRE básico consiste no gerenciamento do estoque do cliente, no estabelecimento da frequência e quantidade de produto entregue, além do roteiro percorrido pela frota de veículos ao longo do horizonte de planejamento. Esta tese propõe uma contribuição ao estudo do PRE em um sistema logístico em três níveis, onde o fornecedor gerencia seu próprio estoque, além dos estoques dos clientes. A pesquisa contempla o caso determinístico, quando as demandas do conjunto de clientes são conhecidas a priori, e o caso estocástico, quando estas informações não são conhecidas preliminarmente. Para o caso determinístico foi desenvolvida uma nova política de distribuição baseada no cálculo de um lote econômico de entrega formulada em três variações, sendo necessidades líquidas, necessidades brutas e distância. Um modelo de programação linear inteira mista binária (PLIMB) foi proposto, incorporando o sistema logístico em três níveis, além de restrições não comumente tratadas, como o dimensionamento da frota de veículos. Novos indicadores de desempenho logístico foram desenvolvidos, permitindo avaliar o desempenho das políticas. Para a resolução do problema, foi desenvolvida uma heurística de duas fases e três estágios. As fases são divididas em etapa construtiva e etapa de refinamento. Na etapa construtiva, o problema é resolvido em três estágios, onde o primeiro é responsável pela programação das entregas, o segundo pelo agrupamento dos pontos de demanda e o terceiro pela roteirização dos clientes nos grupos formados. A fase de refinamento compreende uma estrutura heurística de busca em vizinhança ampla (BVA). Cenários de pequeno, médio e grande porte, com variações no custo de estocagem e de transporte foram gerados a partir de dados da literatura e parametrizados no contexto da pesquisa. A extensão para PRE-estocástico mantém as tratativas para o caso determinístico, com a formulação de uma política de distribuição por lote econômico de entrega como alternativa à estratégia de distribuição além das políticas maximum level (ML) e order-up-to level (OU). A inovação principal repousa na estratégia dinâmica para a previsão de demanda futura, utilizando Redes Neurais de Funções de Bases Radiais (RBFs). O PRE estocástico é ainda escassamente tratado de forma dinâmica na literatura, especialmente quando a demanda futura é obtida por técnicas robustas de previsão. Dessa forma, as RBFs são oportunamente aplicadas ao problema, dada sua eficiência no endereçamento de previsão de séries temporais amplamente corroboradas em outros estudos. Em ambos os casos estudados, uma extensa revisão de literatura posiciona as contribuições da pesquisa. Os resultados computacionais obtidos sobre um conjunto de 144 problemas de pequeno, médio e grande porte, mostraram a viabilidade do emprego das políticas de lote econômico, que dominaram todos os cenários para o problema estocástico. Os indicadores de desempenho logístico possibilitaram novos insights gerenciais ao processo de tomada de decisão, além de suportar o desempenho da política de lote econômico no âmbito qualitativo. Palavras-chave: Roteirização e Estoque; Sistema Logístico em Três Níveis, Determinístico; Estocástico e Dinâmico; Lote Econômico; Heurísticas, Previsão, Redes Neurais de Funções de Bases Radiais.Abstract: In vendor-managed inventory systems, the logistics decisions are centralized at the supplier's level. Its operation requires solving a complex combinatorial optimization problem, called Inventory Routing Problem (IRP), which is to determine the frequency and quantity, delivered to the customer in addition the vehicle routing over a planning horizon. This thesis proposes a contribution to the IRP in a three-echelon logistics system, where the vendor manages the customer's inventories, deciding when, how much and how to serve them over a planning horizon. At the same time, the supplier manages its own inventory level, deciding when and how much replenishes itself, in order to avoid stock out to yourself and to the customers. The research consider the deterministic case, when customer's demands are a priori known, and the stochastic case, when the demands and other details are not known preliminarily. For the deterministic case a new distribution policy has been developed, based on an economic order quantity (EOQ) in three variations, based on net necessity, gross necessity and distance. The EOQ formulation has been addressed to equate the trade-off between transportation and inventory cost arising on order-up-to level (OU) and maximum level (ML) distribution policy. A mixed integer linear programming model (MILP) was formulated for the deterministic IRP, incorporating the three-echelon logistics system features, as well as restrictions not commonly treated, as sizing the vehicle fleet. New logistics performance indicators were developed in order to evaluate policy under a qualitative framework. To solve the problem, a new heuristic approach with two-phase and three-stage was proposed. The phases are divided into constructive phase and improvement stage. In constructive phase, the problem is solved in three stages, where the first is responsible for the delivery scheduling, the second by clustering the demand points and the third by routing customers. The improvement phase comprises in a large neighborhood search procedure (LNS). Small, medium and large scenarios with variations on the inventory and transportation costs were generated, based on data from literature and parameterized in the research context. Extensive computational tests were performed to demonstrate the efficiency of the EOQ proposed distribution policy, the effectiveness of heuristic strategy used and applicability performance indicators. It demonstrated the performance of EOQ policy on OU and ML formulations. The extension to stochastic IRP keeps the same requirements as the deterministic case. A EOQ policy was proposed in addition to the ML and OU policies. The main innovation lies in the dynamic strategy for predicting future demand, using Neural Networks of Radial Basis Function (RBF's). The stochastic IRP is still poorly handled in the literature, especially when the future demand is obtained by robust prediction techniques. Thus, timely RBFs are applied to the problem, given its efficiency in time series forecasting addressing widely corroborated in other studies. In both cases studied, an extensive literature review shows the research contributions. The computational results obtained on a set of 144 small, medium and large problems, showed the viability of using the EOQ policies, which dominated all scenarios for the stochastic problem. Logistics performance indicators enabled new insights to management decision-making process and supports the performance of the EOQ on the qualitative level. Keywords: Inventory Routing; Three-echelon Logistics System; Deterministic, Dynamic and Stochastic, Economic Order Quantity, Forecasting, Radial Basis Functions Neural Networks

Performance evaluation of distribution strategies for the inventory routing problem

International audienceDirect shipping strategy is an easy-to-implement distribution strategy frequently used in industrial distribution systems. In this paper, an analytic method is developed for performance evaluation of the strategy for the infinite horizon inventory routing problem with delivery frequency constraint. With the method, the effectiveness of direct shipping strategy can be represented as a function of some system parameters. We demonstrate that the effectiveness of direct shipping is at least the square root of the smallest utilization ratio of vehicle capacity. This implies that the effectiveness of the strategy can reach 100% (respectively, 94.86%) whenever the demand rate of each retailer is 100% (respectively, 90%) of the vehicle capacity multiplied by the upper bound of the delivery frequency. This insight can help a firm answer questions such as: under what conditions direct shipping strategy is effective and why, and how effective the strategy is under a specific condition? In case direct shipping strategy is proven ineffective, a more general Fixed Partition Policy (FPP) that combines direct shipping strategy and multiple-stop shipping strategy must be used. An analytic method is also developed for performance evaluation of general FPPs. We demonstrate that the effectiveness of an FPP depends on the total demand rate of the retailers in each partition (each retailer set) and their closeness level. This insight provides a useful guideline to the design of effective FPPs. The analytic methods make the performance improvement of a distribution system possible through adjusting its system parameters

Performance evaluation of distribution strategies for the inventory routing problem

Direct shipping strategy is an easy-to-implement distribution strategy frequently used in industrial distribution systems. In this paper, an analytic method is developed for performance evaluation of the strategy for the infinite horizon inventory routing problem with delivery frequency constraint. With the method, the effectiveness of direct shipping strategy can be represented as a function of some system parameters. We demonstrate that the effectiveness of direct shipping is at least the square root of the smallest utilization ratio of vehicle capacity. This implies that the effectiveness of the strategy can reach 100% (respectively, 94.86%) whenever the demand rate of each retailer is 100% (respectively, 90%) of the vehicle capacity multiplied by the upper bound of the delivery frequency. This insight can help a firm answer questions such as: under what conditions direct shipping strategy is effective and why, and how effective the strategy is under a specific condition? In case direct shipping strategy is proven ineffective, a more general Fixed Partition Policy (FPP) that combines direct shipping strategy and multiple-stop shipping strategy must be used. An analytic method is also developed for performance evaluation of general FPPs. We demonstrate that the effectiveness of an FPP depends on the total demand rate of the retailers in each partition (each retailer set) and their closeness level. This insight provides a useful guideline to the design of effective FPPs. The analytic methods make the performance improvement of a distribution system possible through adjusting its system parameters.Logistics Distribution Inventory routing Direct shipping Fixed partitioning policy Worst case analysis