Demand fulfillment in customer hierarchies with stochastic demand

Supply scarcity, due to demand or supply fluctuations, is a common issue in make-to-stock production systems. To increase profits when customers are heterogeneous, firms need to decide whether to accept a customer order or reject it in anticipation of more profitable orders, and if accepted, which supplies to use in order to fulfill the order. Such issues are addressed by solving demand fulfillment problems. In order to provide a solution, firms commonly divide their customers into different segments, based on their respective profitability. The available supply is first allocated to the customer segments based on their projected demand information. Then, as customer orders materialize, the allocated quotas are consumed. The customer segments commonly have a multilevel hierarchical structure, which reflects the structure of the sales organization. In this thesis, we study the demand fulfillment problem in make-to-stock production systems, considering such customer hierarchies with stochastic demand. In the hierarchical setting, the available supply is allocated level by level from top to bottom of the hierarchy by multiple planners on different levels. The planners on higher levels of the hierarchy need to make their allocation decisions based on aggregated information, since transmitting all detailed demand information from the bottom to the top of the hierarchy is not generally feasible. In practice, simplistic rules of thumb are applied to deal with this decentralized problem, which lead to sub-optimal results. We aim to provide more effective approaches that result in near-optimal solutions to this decentralized problem. We first consider the single-period problem with a single supply replenishment and focus on identifying critical information for good, decentralized allocation decisions. We propose two decentralized allocation methods, namely a stochastic Theil index approximation and a clustering approach, which provide near-optimal results even for large, complicated hierarchies. Both methods transmit aggregated information about profit heterogeneity and demand uncertainty in the hierarchy, which is missing in the current simplistic rules. Subsequently, we expand our analysis to a multi-period setting, in which periodic supply replenishments are considered and periods are interconnected by inventory or backlog. We consider a periodic setting, meaning that in each period we allow multiple orders from multiple customer segments. We first formalize the centralized problem as a two-stage stochastic dynamic program. Due to the curse of dimensionality, the problem is computationally intractable. Therefore, we propose an approximate dynamic programming heuristic. For the decentralized case, we consider our proposed clustering method and modify it to fit the multi-period setting, relying on the approximate dynamic programming heuristic. Our results show that the proposed heuristics lead to profits very close to the ex-post optimal solution for both centralized and decentralized problems. Finally, we look into the order promising stage and compare different consumption functions, namely partitioned, rule-based nested, and bid price methods. Our results show that nesting leads to performance improvements compared to partitioned consumption. However, for decentralized problems, the improvement resulting from nesting cannot mitigate the profit loss from considerable mis-allocations made by simplistic rules, except for cases with high demand uncertainty or low profit heterogeneity. Moreover, among the nested consumption functions, the bid price approach, which integrates the allocation and consumption stages, leads to a higher performance than the rule-based consumption methods. Altogether, our proposed decentralized methods lead to drastic profit improvements compared to the current simplistic rules for demand fulfillment in customer hierarchies, except for cases with very low shortage or for largely homogeneous customers, where simplistic rules perform similarly well. Applying our advanced methods is especially important when the shortage rate is high or customers are more heterogeneous. Regarding order promising, nesting is more crucial when demand uncertainty is high. The research presented in this thesis was undertaken as part of the project “demand fulfillment in customer hierarchies”. It was funded by the German Research Foundation (DFG) under grant FL738/2-1

Achieving Breakthrough Service Delivery Through Dynamic Asset Deployment Strategies

Many firms have shifted their focus from their products to their customers and the value derived from owning and using the products. They see after-sales service as an important source of revenue and profit, customer acquisition and retention, and competitive differentiation. However, they also find it challenging to manage their service-supply chain. Service organizations must position and manage service-supply-chain resources optimally to support the delivery of after-sales service. They must also develop capabilities to respond rapidly to the demand for service in a cost-effective manner. To succeed in implementing a service-centric strategy, firms must determine what items in their products’ service bill-of-material hierarchy should be deployed throughout their geographical hierarchy of service support locations. They must make these complex and interrelated decisions in anticipation of service demand, which is uncertain. Firms must also be flexible and should understand the mechanisms in a service-supply chain needed to fulfill customers’ demands for service and the resulting demands for support assets and capacities. Dynamic asset deployment (DAD), a collection of management policies that promote this flexibility, can be used to develop the capabilities needed to effectively and profitably deliver services. These policies require a real-options-based optimization approach to decision making

Exploring wood procurement system agility to improve the forest products industry’s competitiveness

Les difficultés vécus par l'industrie canadienne des produits forestiers dans la dernière décennie l’ont amené vers une transformation importante. L'innovation dans les produits et les processus est encore nécessaire afin de maximiser la valeur économique des ressources forestières. Cette thèse se concentre sur le les systèmes d'approvisionnement en bois de l’industrie forestière qui est responsable de la récolte et de la livraison des matières premières de la forêt vers les usines. Les entreprises les plus compétitives sont celles qui peuvent fournir les bons produits aux bons clients au bon moment. L'agilité du système d'approvisionnement en bois devient ainsi une des caractéristiques nécessaires à la compétitivité. Les objectifs de la thèse sont d'identifier les possibilités d'améliorer l'agilité du système d'approvisionnement en bois, de quantifier les gains potentiels et de proposer un mécanisme dans le but d’anticiper son impact à long terme. L’agilité est la capacité des systèmes d'approvisionnement en bois à répondre rapidement et efficacement à des fluctuations inattendues de la demande. Premièrement, nous identifions les capacités requises par le système d'approvisionnement en bois qui permettent l'agilité; ensuite, nous examinons la littérature portant sur les systèmes d'approvisionnement en bois pour trouver des signes de ces capacités. Suite à cette étape, une opportunité d'améliorer l'agilité des systèmes d'approvisionnement a été identifiée. Celle-ci implique une plus grande flexibilité dans le choix des traitements sylvicoles au niveau opérationnel afin de mieux aligner l'offre avec la demande. Une expérimentation a été menée en utilisant des données industrielles pour quantifier les avantages potentiels associés à l'approche. Dans les scénarios avec flexibilité permise, des profits significativement plus élevés et des taux plus élevés de satisfaction de la demande ont été observés. Ensuite, un système de simulation-optimisation de la planification hiérarchique a été développé pour étudier l'influence de la flexibilité au niveau opérationnel sur l'approvisionnement en bois à long terme. Le système a été mis en œuvre en utilisant les données hypothétiques d'une forêt du domaine public québécois pour un horizon de 100 ans. Le système développé a permis de mesurer les impacts à courts et à long terme des décisions d'approvisionnement. Il devrait permettre de mieux intégrer les pratiques d’aménagements forestiers avec les besoins de la chaîne d’approvisionnement.The significant downfall experienced by the Canadian forest products industry in the past decade has catalyzed the industry into a process of transformation. A concerted effort to maximize economic value from forest resources through innovation in both products and processes is currently underway. This thesis focuses on process innovation of wood procurement systems (WPS). WPS includes upstream processes and actors in the forest products supply chain, responsible for procuring and delivering raw materials from forests to manufacturing mills. The competitiveness of the industry depends on the agility of WPS to deliver the right product to the right customer at the right time. The specific aims of the thesis are to identify opportunities to improve wood procurement system agility, quantify the potential improvement in performance and propose a mechanism to anticipate its long-term impact. Agility is the ability to respond promptly and effectively to unexpected short-term fluctuation in demand. We first identify the capabilities a WPS needs to possess in order to enable agility; we then review the literature in the WPS domain to search for evidence of these capabilities. An opportunity to improve agility of WPS was then identified. It entailed providing managers with flexibility in the choice of silvicultural treatments at the operational level to permit better alignment of supply with the prevailing demand. An experiment was conducted using industry data to quantify the potential benefits associated with the approach. In scenarios where flexibility was permitted, significantly higher profits and demand fulfillment rates were observed. Next, a simulation-optimization system for hierarchical forest management planning was developed to examine the influence of operational level silvicultural flexibility on long-term wood supply. The system was implemented to a forest management unit in Québec in a rolling planning horizon basis for a 100 year horizon. The system demonstrated a capability to measure short and long-term impacts of supply decisions. It will prove to be a useful tool to better integrate forest management practices and supply chain needs

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Coordinated planning in revenue management

Revenue management has been applied in service industries for more than thirty years. Since then, revenue management has been transferred to other industries like manufacturing or e- fulfillment. Short-term revenue management decisions are taken based on other, longer-term decisions such as decisions about actual capacity, segment-based prices or the price fences in place. While optimization approaches have been developed for each of these planning tasks in isolation, existing approaches typically do not consider interactions between planning tasks. This thesis considers coordinated planning in revenue management, that is the interaction of revenue management decisions with other planning tasks. First, we provide an overview of both the literature on coordinated decision making in the context of revenue management in different industries, and the literature on existing frameworks, which aim to structure the planning tasks around revenue management. We find that the planning tasks relevant to revenue management differ across the industries considered. Moreover, planning tasks are relevant on different hierarchical levels in different industries. We discuss an approach for an industry-independent framework. Based on the relevant planning tasks identified, we investigate the long-term performance of revenue management and therefore the integration of revenue management and customer relationship management. We present a stochastic dynamic programming approach, where the firm’s allocation decision impacts future customer demands by influencing the repurchase probabilities of customers, depending on whether their request has been accepted or rejected. We show that a protection level policy is not necessarily optimal in a two-period setting. In a numerical study, we find that the value of looking ahead in time is low on average but may be substantial in some scenarios. However, the benefit from regular demand updates is considerably higher than the additional value of looking ahead in time on average. Lastly, we investigate the interaction of revenue management and fencing. We account for the trade-off between price-driven demand leakage on the one hand and costs for fencing on the other hand. We show that fencing decisions have an impact on the optimal capacity allocation, but that this is not the case vice versa as the fencing decision does not depend on the allocation decision. Taking both decisions sequentially is therefore optimal. We extend our approach in order to account for additional stock-out-based demand substitution. Then, both decisions depend on each other and firms should take both decisions simultaneously

Holonic supply chain:a study from family-based manufacturing perspective

In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler's holonic theory

Management of Stochastic Demand in Make-to-Stock Manufacturing

Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature

An Optimistic-Robust Approach for Dynamic Positioning of Omnichannel Inventories

We introduce a new class of data-driven and distribution-free optimistic-robust bimodal inventory optimization (BIO) strategy to effectively allocate inventory across a retail chain to meet time-varying, uncertain omnichannel demand. While prior Robust optimization (RO) methods emphasize the downside, i.e., worst-case adversarial demand, BIO also considers the upside to remain resilient like RO while also reaping the rewards of improved average-case performance by overcoming the presence of endogenous outliers. This bimodal strategy is particularly valuable for balancing the tradeoff between lost sales at the store and the costs of cross-channel e-commerce fulfillment, which is at the core of our inventory optimization model. These factors are asymmetric due to the heterogenous behavior of the channels, with a bias towards the former in terms of lost-sales cost and a dependence on network effects for the latter. We provide structural insights about the BIO solution and how it can be tuned to achieve a preferred tradeoff between robustness and the average-case. Our experiments show that significant benefits can be achieved by rethinking traditional approaches to inventory management, which are siloed by channel and location. Using a real-world dataset from a large American omnichannel retail chain, a business value assessment during a peak period indicates over a 15% profitability gain for BIO over RO and other baselines while also preserving the (practical) worst case performance