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

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

Decision models for fast-fashion supply and stocking problems in internet fulfillment warehouses

Internet technology is being widely used to transform all aspects of the modern supply chain. Specifically, accelerated product flows and wide spread information sharing across the supply chain have generated new sets of decision problems. This research addresses two such problems. The first focuses on fast fashion supply chains in which inventory and price are managed in real time to maximize retail cycle revenue. The second is concerned with explosive storage policies in Internet Fulfillment Warehouses (IFW). Fashion products are characterized by short product life cycles and market success uncertainty. An unsuccessful product will often require multiple price discounts to clear the inventory. The first topic proposes a switching solution for fast-fashion retailers who have preordered an initial or block inventory, and plan to use channel switching as opposed to multiple discounting steps. The FFS Multi-Channel Switching (MCS) problem then is to monitor real-time demand and store inventory, such that at the optimal period the remaining store inventory is sold at clearance, and the warehouse inventory is switched to the outlet channel. The objective is to maximize the total revenue. With a linear projection of the moving average demand trend, an estimation of the remaining cycle revenue at any time in the cycle is shown to be a concave function of the switching time. Using a set of conditions the objective is further simplified into cases. The Linear Moving Average Trend (LMAT) heuristic then prescribes whether a channel switch should be made in the next period. The LMAT is compared with the optimal policy and the No-Switch and Beta-Switch rules. The LMAT performs very well and the majority of test problems provide a solution within 0.4% of the optimal. This confirms that LMAT can readily and effectively be applied to real time decision making in a FFS. An IFW is a facility built and operated exclusively for online retail, and a key differentiator is the explosive storage policy. Breaking the single stocking location tradition, in an IFW small batches of the same stock keeping unit (SKU) are dispersed across the warehouse. Order fulfillment time performance is then closely related to the storage location decision, that is, for every incoming bulk, what is the specific storage location for each batch. Faster fulfillment is possible when SKUs are clustered such that narrow band picklists can be efficiently generated. Stock location decisions are therefore a function of the demand arrival behavior and correlations with other SKUs. Faster fulfillment is possible when SKUs are clustered such that narrow band picklists can be efficiently generated. Stock location decisions are therefore a function of the demand behavior and correlations with other SKUs. A Joint Item Correlation and Density Oriented (JICDO) Stocking Algorithm is developed and tested. JICDO is formulated to increase the probability that M pick able order items are stocked in a δ band of storage locations. It scans the current inventory dispersion to identify location bands with low SKU density and combines the storage affinity with correlated items. In small problem testing against a MIP formulation and large scale testing in a simulator the JICDO performance is confirmed

Transportation interoperable planning in the context of food supply chain

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

International Logistics

In this study guide the essence, the basic conceptions and the role of international logistics in economic development, the international and organizational aspects of procurement logistics, international warehousing, conceptual foundations of distribution logistics and inernational transport logistics are examined. This study guide is intended for students of specialty “International Economic Relations”

Zara and Benetton: Comparison of two business models

The project analizes and compares two very important and diferent business models in fast fashion industry: Zara y Benetton models. Their models are so diferent but have been a great success, due to their capacity to respond quickly to demand of the market, then due to their flexibility. In this regard, the project also demonstrates how information sharing have a big role to the success of a company. It improves the efficiency of a company and helps to achieve the customer satisfaction . To achieve a good sharing information, it' s important a good and strenght relationship between manufacturer and retailer

Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management