Inventory optimization for perishables subject to supply disruptions

We study a retailer selling perishable products with fixed lifetime. The retailer’s supply system is subject to random disruptions. Assuming a base-stock policy, deterministic demand and stationary cost parameters, we determine the expression for the optimal base-stock level. We show that if the retailer manages to make the system safer, it is possible to operate with the same expected cost even with products with shorter lifetimes. We conclude that the retailer should concentrate on reducing disruptions’ durations instead of their occurrence rate.</p

Containing Risk when Maximizing Supply-Chain Performance

The objective of this dissertation is to develop and test an approach that will quantify the level of risk in the supply chain, evaluate the cost and impact of risk mitigation strategies, validate event management protocols pre-implementation, and optimize across a portfolio of risk mitigation strategies. The research integrates a Mixed Integer Linear Programming (MILP) model and a Discrete Event Simulation model to investigate a production-inventory-transportation problem subject to risk. The MILP model calculates the optimal Net Profit Contribution of the supply chain in the absence of risk. Deviation risks are introduced as volatility in final demand and lead times, with lead time volatility affecting raw material lead times from suppliers to manufacturing plants and finished goods lead times from manufacturing plants to the warehouses. Disruption risks are modelled as temporarily impeding production at the manufacturing plants, in-bound distribution of raw materials from suppliers to the manufacturing plants, and out-bound distribution of finished goods from the manufacturing plants to warehouses. Computational experiments are run to examine the impact of risk on the supply chain. Further experiments explore the consequences of three risk mitigation strategies (inventory placement, expediting, and production flexibility) on supply chain performance in the presence of risk with the aim of discovering whether one strategy dominates or whether a portfolio approach to risk mitigation performs best. In sum, this research seeks to develop a framework that can inform efforts in understanding, planning for and controlling risk in the supply chain

Making smart recommendations for perishable and stockout products

Food waste and stockouts are widely recognized as an important global challenge. While inventory management aims to address these challenges, the tools available to inventory managers are often limited and the usefulness of their decisions is dependent on demand realizations, which are not within their control. Recommender systems (RS) can influence and direct customer demand, e.g., by sending personalized emails with promotions for different items. We propose a novel approach that combines the opportunities provided by RS with inventory management considerations. Under the assumption that there is a known set of customers to receive a promotion consisting of items, we use mixed-integer programming (MIP) to allocate recommended items across customers taking both individual preferences and the current state of inventory with uncertainties into account. Our approach can solve problems with both stochastic supply (inventory and perishability) and demand. We propose heuristics to improve scalability and compare their performance with the optimal solution using data from an online grocery retailer. The goal is to target the right set of customers who are likely to purchase an item, while simultaneously considering which items are prone to expire or be out-of-stock soon. We show that creating recommendation lists exclusively considering user preferences can be counterproductive to users due to possible excessive stockouts. Similarly, focusing only on the retailer can be counterproductive to retailer sales due to the number of expired products that can be considered lost income. We thus avoid the loss of customer goodwill due to stockouts and reduce waste by selling inventory before it expires

Agribusiness supply chain risk management: A review of quantitative decision models

Supply chain risk management is a large and growing field of research. However, within this field, mathematical models for agricultural products have received relatively little attention. This is somewhat surprising as risk management is even more important for agricultural supply chains due to challenges associated with seasonality, supply spikes, long supply lead-times, and perishability. This paper carries out a thorough review of the relatively limited literature on quantitative risk management models for agricultural supply chains. Specifically, we identify robustness and resilience as two key techniques for managing risk. Since these terms are not used consistently in the literature, we propose clear definitions and metrics for these terms; we then use these definitions to classify the agricultural supply chain risk management literature. Implications are given for both practice and future research on agricultural supply chain risk management

Deep Reinforcement Learning for Supply Chain Synchronization

Supply chain synchronization can prevent the “bullwhip effect” and significantly mitigate ripple effects caused by operational failures. This paper demonstrates how deep reinforcement learning agents based on the proximal policy optimization algorithm can synchronize inbound and outbound flows if end-toend visibility is provided. The paper concludes that the proposed solution has the potential to perform adaptive control in complex supply chains. Furthermore, the proposed approach is general, task unspecific, and adaptive in the sense that prior knowledge about the system is not required

A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty

The need for inventory control models for practical real-world applications is growing with the global expansion of supply chains. The widely used traditional optimization procedures usually require an explicit mathematical model formulated based on some assumptions. The validity of such models and approaches for real world applications depend greatly upon whether the assumptions made match closely with the reality. The use of meta-heuristics, as opposed to a traditional method, does not require such assumptions and has allowed more realistic modeling of the inventory control system and its solution. In this dissertation, a metaheuristic-based simulation optimization framework is developed for supply chain inventory management under uncertainty. In the proposed framework, any effective metaheuristic can be employed to serve as the optimizer to intelligently search the solution space, using an appropriate simulation inventory model as the evaluation module. To be realistic and practical, the proposed framework supports inventory decision-making under supply-side and demand-side uncertainty in a supply chain. The supply-side uncertainty specifically considered includes quality imperfection. As far as demand-side uncertainty is concerned, the new framework does not make any assumption on demand distribution and can process any demand time series. This salient feature enables users to have the flexibility to evaluate data of practical relevance. In addition, other realistic factors, such as capacity constraints, limited shelf life of products and type-compatible substitutions are also considered and studied by the new framework. The proposed framework has been applied to single-vendor multi-buyer supply chains with the single vendor facing the direct impact of quality deviation and capacity constraint from its supplier and the buyers facing demand uncertainty. In addition, it has been extended to the supply chain inventory management of highly perishable products. Blood products with limited shelf life and ABO compatibility have been examined in detail. It is expected that the proposed framework can be easily adapted to different supply chain systems, including healthcare organizations. Computational results have shown that the proposed framework can effectively assess the impacts of different realistic factors on the performance of a supply chain from different angles, and to determine the optimal inventory policies accordingly

Disruption Management of Rolling Stock in Passenger Railway Transportation

This paper deals with real-time disruption management of rolling stock in passenger railway transportation. We present a generic framework for modeling disruptions in railway rolling stock schedules. The framework is presented as an online combinatorial decision problem where the uncertainty of a disruption is modeled by a sequence of information updates. To decompose the problem we propose a rolling horizon approach where only rolling stock decisions within a certain time horizon from the time of rescheduling are taken into account. The schedules are then revised as the situation progresses and more accurate information becomes available. We extend an existing model for rolling stock scheduling to the specific requirements of the real-time case and apply it in the rolling horizon framework. We perform computational tests on instances constructed from real life cases and explore the consequences of different settings of the approach for the trade-off between solution quality and computation time

Safety and quality based traceability system for food supply chains

The onset of new technologies and new procedures for food production has reduced the familiarity and capability of consumers to discern the quality of products bought, as well as being unable to verify if all health and safety regulations were complied with. Traceability can be a tool for safety and quality assurance for perishable food as well as for process optimization and economic gain. However, it is often considered mere bureaucracy and an economic burden. Such is prevalent in micro and small-sized (MSE) enterprises. As they constitute most of food sector, the adoption of traceability systems is quite slow and mostly to satisfy legal requirements. In order to determine the main advantages and disadvantages of traceability models, implementation and technologies, a literature review and MSE focused analysis was performed. Economic gains, more quality and safety, better efficiency and a more direct contact with consumers are some of the main advantages. High implementation costs, poorly defined benefits, lack of compatibility, consumer focused perspective and exposure of sensitive information are some of the main issues. With the result of that analysis, a an open-source traceability framework was developed. The framework includes an external communication model and is accompanied by software capable of fulfilling all tasks required for quality assurance both internally and externally. It encompasses whole food supply chains and maintains records of quality and safety while not necessitating mature IT capabilities, uncommon characteristic of MSE’s. It is imperative for traceability systems to have a common structure for information exchange. Without it, these systems lose much of their utility as they will only be usable internally and will have reduced capacity to add value to products and manage recalls. It is also imperative to develop this type of framework by focusing it on existing resources such as HACCP flowcharts to define gateways for quality evaluation. With that in mind, the volume of information is divided between all stakeholders according to their necessities and funding capacities. Most of the information is stored by regulators as they have access to more funding. This improves the ease and flexibility of implementation of traceability systems by the companies. Using all developed tools an hypothetical food supply chain was simulated. The objective of this simulation was to observe all quality variations and capacity to transmit information. It was verified that the developed system was able to evaluate quality throughout an entire chain and to effectively communicate all necessary information.O surgimento de novas tecnologias e novos processos tem reduzido a familiaridade e capacidade dos consumidores em discernir a qualidade dos produtos adquiridos bem como a capacidade de verificar se todas as regras de higiene e segurança foram cumpridas. A rastreabilidade pode ser uma ferramenta capaz de assegurar a segurança e a qualidade de alimentos perecíveis bem como otimização de processos e ganho económico. Ainda assim, é regularmente considerada uma mera burocracia e um fardo económico, princiapalmente pelas micro, pequenas e médias empresas (PME). No entanto, estas constituem a maior parte do sector alimentar e uma vez que a rastreabilidade não é desejada para além do cumprimento de requisitos legais, a adopção de sistemas de rastreabilidade tem sido bastante lenta. De modo a determinar as maiores vantagens e desvantagens dos modelos de rastreabilidade, implementação e tecnologia, foi efectuada uma revisão de literature com crítica focada nas PME. Ganho económico, mais qualidade e segurança, maior eficiência e um contacto mais próximo com os consumidores são algumas das principais vantagens. Elevados custos de implementação, vantagens nem sempre tangíveis e fracamente definidas, falta de compatibilidade, perspectiva focada no consumidor e exposição de informação sensível são algumas das principais desvantagens. Com o resultado desta análise, foi desenvolvida uma estrutra open-source para sistemas de rastreabilidade. Esta estrutura inclui um modelo de comunicação externa e é acompanhada de software capaz de cumprir todas as tarefas requiridas para a garantia de qualidade tanto interna como externamente. Abrange cadeias de abastecimento alimentar inteiras e mantém registos de qualidade e segurança sem necessidade de elevada capacidade em tecnologias de informação, característica incomum das PME. É imperativo que os sistemas de rastreabilidade tenham uma estrutura de troca de informação comum. Sem a mesma, estes sistems perdem muita da sua utilidade pois apenas seriam usados para propósitos internos e isso significa que teriam uma maior dificuldade em auxiliar recolhas de produto impróprio e em adicionar valor aos produtos. É também imperativo que este tipo de estrutura seja desenvolvida com foco em recursos existentes tais como os fluxogramas do sistema HACCP como meio de segmentação de processos e avaliação de qualidade. Com isso em mente, o volume de informação é divido por todas partes de acordo com as suas necessidades e capacidades de financiamento. A maior parte da informação é mantida pelos reguladores devido à sua maior facilidade de acesso a fundos. Isto aumenta a facilidade e flexibilidade de implementação de sistemas de rastreabilidade por parte das empresas. Utilizando todas as ferramentas desenvolvidas foi efectuada uma simulação duma cadeia alimentar hipotética com objetivo de observar todas as variações de qualidade e a capacidade de transmissão de informação. Verfificou-se que o sistema é capaz de avaliar a qualiade e trasnmitir eficazmente toda a informação necessária