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

An asymptotic 98.5%-effective lower bound on fixed partition policies for the inventory-routing problem

AbstractWe consider the Inventory-Routing Problem where n geographically dispersed retailers must be supplied by a central facility. The retailers experience demand for a product at a deterministic rate and incur holding costs for keeping inventory. Distribution is performed by a fleet of capacitated vehicles. The objective is to minimize the average transportation and inventory costs per unit time over the infinite horizon. In this paper, we focus on the set of fixed partition policies. In a fixed partition policy, the retailers are partitioned into disjoint and collectively exhaustive sets. Each set of retailers is served independently of the others and at its optimal replenishment rate. We derive a deterministic (O(n)) lower bound on the cost of the optimal fixed partition policy. A probabilistic analysis of the performance of this bound demonstrates that it is asymptotically 98.5%-effective. That is, as the number of retailers increases, the lower bound is very close to the cost of the optimal fixed partition policy

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

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

Integrating materials supply in strategic mine planning of underground coal mines

In July 2005 the Australian Coal Industry’s Research Program (ACARP) commissioned Gary Gibson to identify constraints that would prevent development production rates from achieving full capacity. A “TOP 5” constraint was “The logistics of supply transport distribution and handling of roof support consumables is an issue at older extensive mines immediately while the achievement of higher development rates will compound this issue at most mines.” Then in 2020, Walker, Harvey, Baafi, Kiridena, and Porter were commissioned by ACARP to investigate Australian best practice and progress made since Gibson’s 2005 report. This report was titled: - “Benchmarking study in underground coal mining logistics.” It found that even though logistics continue to be recognised as a critical constraint across many operations particularly at a tactical / day to day level, no strategic thought had been given to logistics in underground coal mines, rather it was always assumed that logistics could keep up with any future planned design and productivity. This subsequently meant that without estimating the impact of any logistical constraint in a life of mine plan, the risk of overvaluing a mining operation is high. This thesis attempts to rectify this shortfall and has developed a system to strategically identify logistics bottlenecks and the impacts that mine planning parameters might have on these at any point in time throughout a life of mine plan. By identifying any logistics constraints as early as possible, the best opportunity to rectify the problem at the least expense is realised. At the very worst if a logistics constraint was unsolvable then it could be understood, planned for, and reflected in the mine’s ongoing financial valuations. The system developed in this thesis, using a suite of unique algorithms, is designed to “bolt onto” existing mine plans in the XPAC mine scheduling software package, and identify at a strategic level the number of material delivery loads required to maintain planned productivity for a mining operation. Once an event was identified the system then drills down using FlexSim discrete event simulation to a tactical level to confirm the predicted impact and understand if a solution can be transferred back as a long-term solution. Most importantly the system developed in this thesis was designed to communicate to multiple non-technical stakeholders through simple graphical outputs if there is a risk to planned production levels due to a logistics constraint

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