An Integrated Model with Variable Production and Demand Rate under Inflation

AbstractIn this article, an integrated model is developed in which a manufacturer purchases raw materials from a supplier, and then produces finished products/goods, after that delivers them to a buyer. In the intended model production rate is assumed as a function of demand rate and customer demand rate is time dependent. To make the model more realistic the effect of inflation and time value of money is also taken into consideration. The concept of the model is illustrated through the numerical example and sensitivity analysis with respect to the system parameters is also performed

Sustainable Inventory Management Model for High-Volume Material with Limited Storage Space under Stochastic Demand and Supply

Inventory management and control has become an important management function, which is vital in ensuring the efficiency and profitability of a company’s operations. Hence, several research studies attempted to develop models to be used to minimise the quantities of excess inventory, in order to reduce their associated costs without compromising both operational efficiency and customers’ needs. The Economic Order Quantity (EOQ) model is one of the most used of these models; however, this model has a number of limiting assumptions, which led to the development of a number of extensions for this model to increase its applicability to the modern-day business environment. Therefore, in this research study, a sustainable inventory management model is developed based on the EOQ concept to optimise the ordering and storage of large-volume inventory, which deteriorates over time, with limited storage space, such as steel, under stochastic demand, supply and backorders. Two control systems were developed and tested in this research study in order to select the most robust system: an open-loop system, based on direct control through which five different time series for each stochastic variable were generated, before an attempt to optimise the average profit was conducted; and a closed-loop system, which uses a neural network, depicting the different business and economic conditions associated with the steel manufacturing industry, to generate the optimal control parameters for each week across the entire planning horizon. A sensitivity analysis proved that the closed-loop neural network control system was more accurate in depicting real-life business conditions, and more robust in optimising the inventory management process for a large-volume, deteriorating item. Moreover, due to its advantages over other techniques, a meta-heuristic Particle Swarm Optimisation (PSO) algorithm was used to solve this model. This model is implemented throughout the research in the case of a steel manufacturing factory under different operational and extreme economic scenarios. As a result of the case study, the developed model proved its robustness and accuracy in managing the inventory of such a unique industry

Grocery omnichannel perishable inventories: performance measures and influencing factors

Purpose- Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures. Design/methodology/approach- The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation. Findings- Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects. Practical implications- To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products. Originality/value- This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors

Responsible Inventory Models for Operation and Logistics Management

The industrialization and the subsequent economic development occurred in the last century have led industrialized societies to pursue increasingly higher economic and financial goals, laying temporarily aside the safeguard of the environment and the defense of human health. However, over the last decade, modern societies have begun to reconsider the importance of social and environmental issues nearby the economic and financial goals. In the real industrial environment as well as in today research activities, new concepts have been introduced, such as sustainable development (SD), green supply chain and ergonomics of the workplace. The notion of “triple bottom line” (3BL) accounting has become increasingly important in industrial management over the last few years (Norman and MacDonald, 2004). The main idea behind the 3BL paradigm is that companies’ ultimate success should not be measured only by the traditional financial results, but also by their ethical and environmental performances. Social and environmental responsibility is essential because a healthy society cannot be achieved and maintained if the population is in poor health. The increasing interest in sustainable development spurs companies and researchers to treat operations management and logistics decisions as a whole by integrating economic, environmental, and social goals (Bouchery et al., 2012). Because of the wideness of the field under consideration, this Ph.D. thesis focuses on a restricted selection of topics, that is Inventory Management and in particular the Lot Sizing problem. The lot sizing problem is undoubtedly one of the most traditional operations management interests, so much so that the first research about lot sizing has been faced more than one century ago (Harris, 1913). The main objectives of this thesis are listed below: 1) The study and the detailed analysis of the existing literature concerning Inventory Management and Lot Sizing, supporting the management of production and logistics activities. In particular, this thesis aims to highlight the different factors and decision-making approaches behind the existing models in the literature. Moreover, it develops a conceptual framework identifying the associated sub-problems, the decision variables and the sources of sustainable achievement in the logistics decisions. The last part of the literature analysis outlines the requirements for future researches. 2) The development of new computational models supporting the Inventory Management and Sustainable Lot Sizing. As a result, an integrated methodological procedure has been developed by making a complete mathematical modeling of the Sustainable Lot Sizing problem. Such a method has been properly validated with data derived from real cases. 3) Understanding and applying the multi-objective optimization techniques, in order to analyze the economic, environmental and social impacts derived from choices concerning the supply, transport and management of incoming materials to a production system. 4) The analysis of the feasibility and convenience of governmental systems of incentives to promote the reduction of emissions owing to the procurement and storage of purchasing materials. A new method based on the multi-objective theory is presented by applying the models developed and by conducting a sensitivity analysis. This method is able to quantify the effectiveness of carbon reduction incentives on varying the input parameters of the problem. 5) Extending the method developed in the first part of the research for the “Single-buyer” case in a "multi-buyer" optics, by introducing the possibility of Horizontal Cooperation. A kind of cooperation among companies in different stages of the purchasing and transportation of raw materials and components on a global scale is the Haulage Sharing approach which is here taken into consideration in depth. This research was supported by a fruitful collaboration with Prof. Robert W. Grubbström (University of Linkoping, Sweden) and its aim has been from the beginning to make a breakthrough both in the theoretical basis concerning sustainable Lot Sizing, and in the subsequent practical application in today industrial contexts

A Lot Sizing Model for a Deteriorating Product with Shifting Production Rates, Freshness, Price, and Stock-Dependent Demand with Price Discounting

Many production systems need to be able to change the rate at which they manufacture products for various reasons, hence, the need to find the optimal lot size under these multiple levels of production. This research addresses the need for optimizing inventory in a system with a shifting production rate and other challenging product characteristics such as product deterioration with limited life span, and product demand that is dependent on the stock level, the state of freshness of the product, and the selling price. The product also needs to be discounted as it gets close to the expiry date in order to boost demand and prevent wastage beyond its life span. Our objective is to maximize profit by determining the optimal selling price and inventory cycle time by deriving the relevant equations for these decision variables. The Newton-Raphson method was used to numerically solve for the optimal values of these variables. Sensitivity analyses were performed to derive useful insights for managerial decision-making

Modelling and Determining Inventory Decisions for Improved Sustainability in Perishable Food Supply Chains

Since the introduction of sustainable development, industries have witnessed significant sustainability challenges. Literature shows that the food industry is concerned about its need for efficient and effective management practices in dealing with perishability and the requirements for conditioned storage and transport of food products that effect the environment. Hence, the environmental part of sustainability demonstrates its significance in this industrial sector. Despite this, there has been little research into environmentally sustainable inventory management of deteriorating items. This thesis presents mathematical modelling based research for production inventory systems in perishable food supply chains. In this study, multi-objective mixed-integer linear programming models are developed to determine economically and environmentally optimal production and inventory decisions for a two-echelon supply chain. The supply chain consists of single sourcing suppliers for raw materials and a producer who operates under a make-to-stock or make-to-order strategy. The demand facing the producer is non-stationary stochastic in nature and has requirements in terms of service level and the remaining shelf life of the marketed products. Using data from the literature, numerical examples are given in order to test and analyse these models. The computational experiments show that operational adjustments in cases where emission and cost parameters were not strongly correlated with supply chain collaboration (where suppliers and a producer operate under centralised control), emissions are effectively reduced without a significant increase in cost. The findings show that assigning a high disposal cost, limit or high weight of importance to perished goods leads to appropriate reduction of expected waste in the supply chain with no major cost increase. The research has made contributions to the literature on sustainable production and inventory management; providing formal models that can be used as an aid to understanding and as a tool for planning and improving sustainable production and inventory control in supply chains involving deteriorating items, in particular with perishable food supply chains.the Ministry of Science and Technology, the Royal Thai Government

Transportation interoperable planning in the context of food supply chain

L'alimentation est une nécessité de base de l'être humain, dont la survie dépend de la quantité et de la qualité de la nourriture ingérée. L'augmentation de la population requiert de plus en plus de nourriture, tandis que la qualité est associée aux contraintes des produits alimentaires comme une courte durée de vie ou la sensibilité à la température. L'augmentation de la demande entraîne une augmentation de la production alimentaire, répartie entre plusieurs sites de production appartenant à plusieurs entreprises de taille variée, qui peuvent utiliser les produits d'autres sites pour fabriquer leurs produits finaux. En outre, certains produits alimentaires doivent être transportés entre les sites et les produits finaux distribués à des détaillants et des consommateurs lointains en tenant compte des contraintes de produits alimentaires. Les activités exercées par ces entités incluent entre autres la production, la distribution, la vente, etc. et ces entités forment conjointement dans l'environnement de l'écosystème alimentaire une chaîne pour le traitement, l'emballage ou la livraison de nourriture. Ce réseau s'appelle une chaîne logistique alimentaire (FSC). En raison de leur nature distribuée, les FSC héritent des problèmes classiques des chaînes logistiques, mais doivent en plus gérer les problèmes découlant de la périssabilité des produits. Cette périssabilité rend extrêmement important le traitement d'enjeux tels que le maintien de la qualité, la prévision de la demande, la gestion des stocks (éviter les ruptures de stock ou les stocks excessifs), l’amélioration de l'efficacité du réapprovisionnement, de la production et du transport, la traçabilité et le suivi pour réagir aux perturbations. Il est donc nécessaire d'établir une collaboration entre les entités principales de l'écosystème alimentaire pour traiter tous ces enjeux. En outre, depuis l'arrivée des entreprises de transport spécialisées, un nouveau acteur a émergé appelé transporteur ou fournisseur de logistique. Ces transporteurs doivent collaborer avec les producteurs, les détaillants et même d'autres transporteurs afin de prendre en compte la demande future et les tendances, afin d'organiser leur réseau et les ressources, pour livrer des produits alimentaires en assurant sécurité et qualité. Ainsi, la collaboration est devenue vitale pour les FSC. La collaboration implique une bonne compréhension des informations échangées afin de minimiser les déplacements, le coût et la pollution environnementale. Des problèmes d'interopérabilité surgissent lorsque les partenaires impliqués utilisent des systèmes hétérogènes et différentes normes et terminologies. Les approches de collaborations existantes comme "Vendor Managed Inventory" (VMI) ou "Collaborative Planning Forecasting and Replenishment" (CPFR) ne prennent en compte que deux acteurs de la FSC : le producteur et le détaillant (acheteur et vendeur). En outre, elles ne considèrent pas la planification de la production et des transports comme des tâches de collaboration. En tenant compte des limitations ci-dessus, nous proposons, dans une première partie de cette thèse, une extension du modèle CPFR prennant en compte les aspects production et transport. Ce nouveau modèle C-PRIPT (Collaborative -Planning Replenishment Inventory Production and Transportation) inclut le transporteur et considère la planification de la production et des transports comme des activités de collaboration. Dans la deuxième partie, nous proposons un modèle distribué et interopérable I-POVES (Interoperable - Path Finder, Order, Vehicle, Environment and Supervisor) pour réaliser la planification des transports en collaboration avec les producteurs, les transporteurs et les détaillants, visant à une meilleure utilisation efficace des ressources de transport. Enfin, nous illustrons le fonctionnement du modèle I-POVES en l’appliquant sur un cas étude de chaîne logistique alimentaire. ABSTRACT : Eating is human’s basic necessity whose survival depends on both quantity and quality of food. Increasing population requires increasing in quantity of food, while quality is associated with the food product constraints like short shelf-life, temperature sensitiveness, climate etc. Increasing demand causes increase in food production, which is distributed between several production sites involving several distinct entities from small to large enterprises, where sites may use the intermediate products of other sites to produce the final products. Moreover, food products need to be transported between sites and final products to be distributed to faraway retailer sites and consumers considering the food product constraints. Activities performed by these entities include but not limited to: production, distribution, sales, etc. and these entities form jointly in the environment of food ecosystem a chain for food gathering, processing, packaging, delivery etc. This distributed network of enterprises is called food supply chain (FSC). Due to FSC’s distributed nature, it inherits not only the common problems also faced by other supply chain, but in addition has to deal with the problems arising from the perishability of food products. This perishability nature makes extremely important for FSC, the handling of issues such as maintaining the quality of food products, forecasting the product demand, managing the inventory according to the forecast to reduce out of stock or excessive inventory of products, improving the efficiency of replenishment, production and transportation, taking into account product future demand and tracing and tracking to react to disturbance. Finally, it is necessary to institute collaboration between the main entities of food ecosystem to deal with all of these issues. Furthermore, since the advent of specialized transport enterprises, a new actor has emerged called transporter or logistics provider in the FSC. These transporters have to collaborate with producers, retailers and even other transporters within FSC to take into account product future demands and trends to organise their transport network and resources to make possible the delivery of the food products with security, while maintaining the quality of the food products. Thus, collaboration became vital for FSC. Collaboration involves a good understanding of exchanged information in order to minimizing number of transport travels, cost and environmental pollution. Interoperability problem arises when each of the partners involved in FSC uses heterogeneous systems and uses different standards and terminologies for representing locations, product constraints, vehicles types etc. Furthermore, existing collaborative approaches like Quick Response, Efficient Consumer Response, Vendor Managed Inventory, Collaborative Planning Forecasting and Replenishment (CPFR), etc. take into account only two types of actors of FSC: buyer and seller (producer and retailer). Additionally, they don’t consider the production and transportation planning as collaborative tasks. Taking into account above limitations, we propose, in the first phase of this thesis, an extension of CPFR model, which take into account production and transportation aspects. This new model C-PRIPT (Collaborative -Planning Replenishment Inventory Production and Transportation) includes transporter actor and elaborates production and transportation planning as collaborative activities. In the second phase, we propose a distributed and interoperable transportation planning model I-POVES (Interoperable - Path Finder, Order, Vehicle, Environment and Supervisor) to realise collaborative transportation planning by collaborating producers, transporters and retailers, aiming at a better use of transport resources. Finally, we illustrate the functioning of I-POVES model by applying it on a case study of food supply chain