Supply chain network design for the diffusion of a new product

Supply Chain Network Design (SCND) deals with the determination of the physical configuration and infrastructures of the supply chain. Specifically, facility location is one of the most critical decisions: transportation, inventory and information sharing decisions can be readily re-optimized in response to changes in the context, while facility location is often fixed and difficult to change even in the medium term. On top of this, when designing a supply network to support a new product diffusion (NPD), the problem becomes both dynamic and stochastic. While literature concentrated on approaching SCND for NPD separately coping with dynamic and stochastic issues, we propose an integrated optimisation model, which allows warehouse positioning decisions in concert with the demand dynamics during the diffusion stage of an innovative product/service. A stochastic dynamic model, which integrates a Stochastic Bass Model (SBM) in order to better describe and capture demand dynamics, is presented. A myopic policy is elaborated in order to solve and validate on the data of a real case of SCND with 1,400 potential market points and 28 alternatives for logistics platforms

Solving closed-loop supply chain problems using game theoretic particle swarm optimisation

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods

Optimal scope of supply chain network & operations design

The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are significant and that has attracted considerable research attention since the late 1990s. This doctoral thesis focuses on developing manageable and realistic optimization models for solving four contemporary and interrelated supply chain network and operations design problems. Each requires an integrated decision-making approach for advancing supply chain effectiveness and efficiency. The first model formulates the strategic robust downsizing of a global supply chain network, which requires an integrated decision-making on resource allocation and network reconfiguration, given certain financial constraints. The second model also looks at the strategic supply chain downsizing problem but extends the first model to include product portfolio selection as a downsizing decision. The third model concerns the redesign of a warranty distribution network, which requires an integrated decision-making on strategic network redesign and tactical recovery process redesign. The fourth model simultaneously determines the operational-level decisions on job assignment and process sequence in order to improve the total throughput of a production facility unit

Production planning mechanisms in demand-driven wood remanufacturing industry

L'objectif principal de cette thèse est d'étudier le problème de planification de la production dans le contexte d'une demande incertaine, d’un niveau de service variable et d’approvisionnements incontrôlables dans une usine de seconde transformation du bois. Les activités de planification et de contrôle de production sont des tâches intrinsèquement complexes et difficiles pour les entreprises de seconde transformation du bois. La complexité vient de certaines caractéristiques intrinsèques de cette industrie, comme la co-production, les procédés alternatifs divergents, les systèmes de production sur commande (make-to-order), des temps de setup variables et une offre incontrôlable. La première partie de cette thèse propose une plate-forme d'optimisation/simulation permettant de prendre des décisions concernant le choix d'une politique de planification de la production, pour traiter rapidement les demandes incertaines, tout en tenant compte des caractéristiques complexes de l'industrie de la seconde transformation du bois. À cet effet, une stratégie de re-planification périodique basée sur un horizon roulant est utilisée et validée par un modèle de simulation utilisant des données réelles provenant d'un partenaire industriel. Dans la deuxième partie de cette thèse, une méthode de gestion des stocks de sécurité dynamique est proposée afin de mieux gérer le niveau de service, qui est contraint par une capacité de production limitée et à la complexité de la gestion des temps de mise en course. Nous avons ainsi développé une approche de re-planification périodique à deux phases, dans laquelle des capacités non-utilisées (dans la première phase) sont attribuées (dans la seconde phase) afin de produire certains produits jugés importants, augmentant ainsi la capacité du système à atteindre le niveau de stock de sécurité. Enfin, dans la troisième partie de la thèse, nous étudions l’impact d’un approvisionnement incontrôlable sur la planification de la production. Différents scénarios d'approvisionnement servent à identifier les seuils critiques dans les variations de l’offre. Le cadre proposé permet aux gestionnaires de comprendre l'impact de politiques d'approvisionnement proposées pour faire face aux incertitudes. Les résultats obtenus à travers les études de cas considérés montrent que les nouvelles approches proposées dans cette thèse constituent des outils pratiques et efficaces pour la planification de production du bois.The main objective of this thesis is to investigate the production planning problem in the context of uncertain demand, variable service level, and uncontrollable supply in a wood remanufacturing mill. Production planning and control activities are complex and represent difficult tasks for wood remanufacturers. The complexity comes from inherent characteristics of the industry such as divergent co-production, alternative processes, make-to-order, short customer lead times, variable setup time, and uncontrollable supply. The first part of this thesis proposes an optimization/simulation platform to make decisions about the selection of a production planning policy to deal swiftly with uncertain demands, under the complex characteristics of the wood remanufacturing industry. For this purpose, a periodic re-planning strategy based on a rolling horizon was used and validated through a simulation model using real data from an industrial partner. The computational results highlighted the significance of using the re-planning model as a practical tool for production planning under unstable demands. In the second part, a dynamic safety stock method was proposed to better manage service level, which was threatened by issues related to limited production capacity and the complexity of setup time. We developed a two-phase periodic re-planning approach whereby idle capacities were allocated to produce more important products thus increasing the realization of safety stock level. Numerical results indicated that the solution of the two-phase method was superior to the initial method in terms of backorder level as well as inventory level. Finally, we studied the impact of uncontrollable supply on demand-driven wood remanufacturing production planning through an optimization and simulation framework. Different supply scenarios were used to identify the safety threshold of supply changes. The proposed framework provided managers with a novel advanced planning approach that allowed understanding the impact of supply policies to deal with uncertainties. In general, the wood products industry offers a rich environment for dealing with uncertainties for which the literature fails to provide efficient solutions. Regarding the results that were obtained through the case studies, we believe that approaches proposed in this thesis can be considered as novel and practical tools for wood remanufacturing production planning

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Bullwhip Effect of a Closed Leep Supply Chain with and Without Information Sharing of Customer Demand

In recent years, companies have become interested in a closed-loop supply chain that is concerned with the recovery pipeline. The expenses of a company can be influenced by large inventories and backlogs due to the bullwhip effect in the supply chain. Previous literature has shown that the bullwhip effect can be decreased by a reverse supply chain. This paper develops a closed-loop supply chain including seven echelons for recovery of end-of-life products. The model considers the order-up-to inventory policy and the exponential smoothing forecasting with a trend method in the system to assist in determining the ordering quantities. The best of the best is the method for this paper to choose a good smoothing parameter and to compare the necessity for information sharing. This test method provides the minimizing cost for the companies and analyzes the type of costs that can be reduced by selecting a good parameter value or utilizing information sharing. Furthermore, it also provides a way to reduce the bullwhip effect and verifies that the bullwhip index and cost are a complement to each other

UNCERTAINTY AS AN ANTECEDENT OF THE SUPPLY CHAIN RISK: DOES SUPPLY CHAIN FLEXIBILITY MATTER IN RISK MITIGATION?

Purpose: This study aims to address the existing research gap, as well as to explore the various types of flexibility which could contribute in mitigating supply chain risks. Methodology: In this regard, we consider three aspects under SCR namely; manufacturing process risk, delivery risk, and supply risk. The study explores the relationships among supply chain risk and environmental uncertainty, and the moderating role of supply chain flexibility by employing data of 91 manufacturing companies and develop a structural equation modelling. Results: Developing economies are contributing well in the global trade and are responsible for 50% of the generated global output. They present future prospects for economic growth and pose challenges mainly because of immature supply chain operations. Considering the critical role of emerging economies in global supply chain, such as India and China, it is also important to observe the moderating and driving supply chain risk factors in these regions. It is assumed that this study will not only fill the existing gap in the literature of SCRM but will assist researchers and practicing managers, by enabling them to fully understand certain types of supply chain flexibility, thus reducing the SCR under business environments

Food industry supply chain planning with product quality indicators

Quantitative supply chain modelling has contributed substantially to a number of fields, such as the automotive industry, logistics and computer hardware. The inherent methods and optimisation techniques could also be explored in relation to the food industry in order to offer potential benefits. One of the major issues of the food industry is to overcome supply seasonality and on-shelf demand. On the shelf demand is the consumer’s in store demand which could also be seasonal. Objective of this work is to add flexibility to seasonal products (i.e. soup) in order to meet the on-shelf demand. In order to achieve this, a preparation process is introduced and integrated into the manufacturing system. This process increases the shelf-life of raw materials before starting the production process. This process, however, affects the quality of fresh raw materials and requires energy. Therefore, a supply chain model is developed, which is based on the link between the quality of the raw material and the processing conditions, which have an effect on the process’ energy consumption and on the overall product quality. It is challenging to quantify the quality by looking at the processing conditions (degrees of freedom) and by linking it with energy in order to control and optimise the quality and energy consumption for each product. The degrees of freedom are defined differently for each process and state. Therefore, the developed model could be applied to all states and processes in order to generate an optimum solution. Moreover, based on the developed model, we have determined key factors in the whole chain, which are most likely to affect the product quality and consequently overall demand. There are two main quality indicator classes to be optimised, which are both considered in the model: static and time dependent indicators. Also, this work considers three different preparation processes – the air-dry, freeze-dry and freezing process – in order to increase the shelf-life of fresh raw materials and to add flexibility to them. A model based on the interrelationship between the quality and the processing conditions has been developed. This new methodology simplifies and enables the model to find the optimum processing conditions in order to obtain optimum quality across all quality indicators, whilst ensuring minimum energy consumption. This model is later integrated into the supply chain system, where it generates optimum solutions, which are then fed into the supply chain model. The supply chain model optimises the quality in terms of customer satisfaction, energy consumption and wastage of the system linked to environmental issues, and cost, so that the final products are more economical. In this system, both the manufacturing and inventory systems are optimised. This model is later implemented with a real world industrial case study (provided by the industrial collaborator). Two case studies are considered (soya milk and soup) and interestingly enough only one of them (soup) corresponds with this model. The advantage of this model is that it compares the two systems and then establishes which system generates an optimum end product.Open Acces