In this thesis, we study three applications of dynamic resource allocation: the first two consider dynamic lead-time quotation in make-to-order (MTO) systems with substitutable products and order cancellations, respectively; and the third application is a manpower allocation problem with job-teaming constraints. Matching supply and demand for manufacturing and service industries has been a fundamental focus of operations management literature, which concentrated on optimizing or improving supply-side decisions since demand has generally been assumed to be exogenously determined. However, recent business trends and advances in consumer behavior modeling have shown that demand for goods and services can clearly be shaped by various decisions that a firm makes, such as price and lead-time. In fact, competition between companies is no longer mainly based on price or product features; lead-time is one of the strategic measures to evaluate suppliers. In MTO manufacturing or service environments that aim to satisfy the customers' unique needs, lead-time quotation impacts the actual demand of the products and the overall profitability of the firm. In the first two parts of the thesis, we study the dynamic lead-time quotation problem in pure MTO (or service) systems characterized by lead-time sensitive Poisson demand and exponentially distributed service times. We formulate the problem as an infinite horizon Markov decision process (MDP) with the objective of maximizing the long-run expected average profit per unit time, where profits are defined to specifically account for delays in delivery of the customer orders. We study dynamic lead-time quotation problem in two particular settings; one setting with the possibility of demand substitution and another setting with order cancellations. The fundamental trade-off in lead-time quotation is between quoting short lead-times and attaining them. In case of demand substitution, i.e., in presence of substitutable products and multiple customer classes with different requirements and margins, this trade-off also includes capacity allocation and order acceptance decisions. In particular, one needs to decide whether to allocate capacity to a low-margin order now, or whether to reserve capacity for potential future arrivals of high-margin orders by considering customer preferences, the current workload in the system, and the future arrivals. In the case of order cancellations, one needs to take into account the probability of cancellation of orders currently in the system and quote lead-times accordingly; otherwise quotation of a longer lead-time may result in the loss of customer order, lower utilization of resources, and, in turn, reduced in profits. In Chapter 2, we study a dynamic lead-time quotation problem in a MTO system with two (partially) substitutable products and two classes of customers. Customers decide to place an order on one of the products or not to place an order, based on the quoted lead-times. We analyze the optimal profit and the structure of the optimal lead-time policy. We also compare the lead-time quotes and profits for different quotation strategies (static vs. dynamic) with or without substitution. Numerical results show that substitution and dynamic quotation have synergetic effects, and higher benefits can be obtained by dynamic quotation and/or substitution when difference in product revenues or arrival rates, or total traffic intensity are higher. In Chapter 3, we study a dynamic lead-time quotation problem in a MTO system with single product considering the order cancellations. The order cancellations can take place during the period that the order is being processed (either waiting or undergoing processing), or after the processing is completed, at the delivery to the customer. We analyze the behavior of optimal profit in terms of cancellation parameters. We show that the optimal profit does not necessarily decrease as cancellation rate increases through a numerical study. When the profit from a cancelled order, arrival rate of customers, or lead-time sensitivity of customers are high, there is a higher probability that optimal profit increases as cancellation rate increases. We also compare the cancellation scenarios with the corresponding no-cancellation scenarios, and show that there exists a cancellation scenario that is at least as good in terms of profit than a no-cancellation scenario for most of the parameter settings. In Chapter 4, we study the Manpower Allocation Problem with Job-Teaming Constraints with the objective of minimizing the total completion time of all tasks. The problem arises in various contexts where tasks require cooperation between workers: a team of individuals with varied expertise required in different locations in a business environment, surgeries requiring different composition of doctors and nurses in a hospital, a combination of technicians with individual skills needed in a service company. A set of tasks at random locations require a set of capabilities to be accomplished, and workers have unique capabilities that are required by several tasks. Tasks require synchronization of workers to be accomplished, hence workers arriving early at a task have to wait for other required workers to arrive in order to start processing. We present a mixed integer programming formulation, strengthen it by adding cuts and propose heuristic approaches. Experimental results are reported for low and high coordination levels, i.e., number of workers that are required to work simultaneously on a given task.

Parallèlement au prix, le délai de livraison est un facteur clé de compétitivité pour les entreprises. De plus les entreprises sont plus que jamais obligées de respecter ce délai promis. La combinaison du choix du prix et du délai promis implique de nouveaux compromis et offre de nombreuses perspectives. Un délai plus court peut entraîner une augmentation de la demande, mais augmente également le risque de livraison tardive et donc décourager les clients. A contrario un délai plus long ou un prix plus élevé entraîne généralement une baisse de la demande. Or malgré le rôle stratégique conjoint du prix et des délais et leurs impacts sur la demande, dans la littérature en gestion des opérations on suppose très généralement une demande exogène (fixée a priori) même si la conception de la chaîne impacte fortement les délais (localisation des sites, positionnement des stocks,..) et donc la demande. Nous nous sommes donc intéressés à ces choix de fixation des délais promis et du prix dans un contexte de demande endogène.La littérature traitant du choix du délai et du prix sous demande endogène a principalement considéré un contexte de fabrication à la commande (Make to Order). Un papier fondateur de Palaka et al en 1998 a présenté cette problématique avec une modélisation de l’entreprise par une file d’attente M/M/1 et nos travaux se placent dans la suite de ce travail. Notre revue de la littérature a permis d'identifier de nouvelles perspectives et nous proposons trois extensions dans cette thèse.Dans notre première contribution, en utilisant le cadre de Palaka et al, nous considérons que le coût de production est une fonction décroissante du délai. Dans tous les articles publiés dans ce contexte, le coût de production unitaire a été supposé constant. Pourtant en pratique, le coût de production unitaire dépend du délai promis, l'entreprise pouvant mieux gérer le processus de production et réduire les coûts de production en proposant des délais plus longs aux clients.Dans la deuxième contribution, nous considérons toujours le cadre de Palaka et al, mais modélisons l'entreprise comme une file d'attente M/M/1/K, pour laquelle la demande est donc rejetée s'il y a déjà K clients dans le système. Dans la littérature issue du travail de Palaka seule la file d'attente M/M/1 a été utilisée, ce qui signifie que tous les clients sont acceptés, ce qui peut entraîner de longues durées de séjour dans le système. Notre idée est basée sur le fait que rejeter certains clients, même si cela peut apparaitre dans un premier temps comme une perte de demande, pourrait aider à proposer un délai plus court pour les clients acceptés, et finalement conduire à une demande et donc un profit plus élevé.Dans la troisième contribution nous étudions un nouveau cadre pour le problème du délai et du prix en fonction de la demande endogène, en modélisant une chaîne logistique composée de deux étapes de production, modélisée par un réseau de files d’attente tandem (M/M/1-M/M/1). Dans la littérature avec ce cadre multi-entreprise, tous les articles ont considéré qu'un seul acteur avait des opérations de production, l'autre acteur ayant un délai nul. Nous avons étudié les scénarios centralisés et décentralisés.Pour chacun des nouveaux problèmes nous avons proposé des formulations maximisant le profit composé du revenu diminué des coûts de production, de stockage et pénalité de retard, et fourni des résolutions optimales, analytiques ou numériques. Ces résolutions nous ont amenés à démontrer de nouveaux résultats (retard moyen dans une M/M/1/K ; condition pour que des contraintes de service locales permettent d’assurer une contrainte de service globale dans un système en tandem). Nous avons mené des expériences numériques pour voir l’influence des différents paramètres. / Along with the price, the delivery lead time has become a key factor of competitiveness for companies and an important purchase criterion for many customers. Nowadays, firms are more than ever obliged to meet their quoted lead time, which is the delivery lead time announced to the customers. The combination of pricing and lead time quotation implies new trade-offs and offers opportunities for many insights. For instance, on the one hand, a shorter quoted lead time can lead to an increase in the demand but also increases the risk of late delivery and thus may affect the firm’s reputation and deter future customers. On the other hand, a longer quoted lead time or a higher price generally yields a lower demand. Despite the strategic role of joint pricing and lead time quotation decisions and their impacts on demand, in the operations management literature an exogenous demand (a priory a known demand) is generally used in supply chain models, even if the design of the supply chain has a strong impact on lead times (i.e., sites location, inventory position, etc.) and thus affects the demand. Therefore, we are interested in the lead time quotation and pricing decisions in a context of endogenous demand (i.e., demand sensitive to price and quoted lead time).The literature dealing with pricing and lead time quotation under an endogenous demand mainly considered a make to order (MTO) context. A pioneer paper, Palaka et al. (1998), investigated this issue by modeling the company as an M/M/1 queue, and our work follows their footsteps. Our review of the literature allowed to identify new perspectives for this problem, which led to three main contributions in this thesis.In our first contribution, using Palaka et al.’s framework, we consider the unit production cost to be a decreasing function in quoted lead time. In most published papers, the unit production cost was assumed to be constant. In practice, the unit production cost generally depends on the quoted lead time. Indeed, the firm can manage better the production process and reduce the production cost by quoting longer lead time to the customers.In the second contribution, we still consider Palaka et al.’s framework but model the firm as an M/M/1/K queue, for which demand is rejected if there are already K customers in the system. In the literature on single firm setting following Palaka et al.’s research, only the M/M/1 queue was used, i.e., where all customers are accepted, which might lead to long sojourn times in the system. Our idea is based on the fact that rejecting some customers, might help to quote shorter lead time for the accepted ones, which might finally lead to a higher profitability, even if in the first glance we lose some demand.In the third contribution, we study a new framework for the lead time quotation and pricing problem under endogenous demand as we model the supply chain by two production stages in a tandem queue (M/M/1-M/M/1). In the literature with multi-firm setting, all papers considered that only one actor has production operations and the other actor has zero lead time. We investigated both the centralized and decentralized decision settings.For each problem studied, we formulated a profit-maximization model, where the profit consists of a revenue minus the production, storage and lateness penalty costs, and provides the optimum result (analytically or numerically). These resolutions led us to demonstrate new theoretical results (such as the expected lateness in an M/M/1/K, and the sufficient condition required to satisfy the global service constraint in a tandem queue by only satisfying the local service constraints). We also conducted numerical experiments and derived managerial insights.

Advancements in information technology enabled to track real time data in a more accurate and precise way in many manufacturing facilities. However, before obtaining the more accurate and precise data, the investment in information technology should be validated. Value of information may be adopted as a criterion in this investment. In this study, we analyze the value of information in a manufacturing facility where production and lead time quotation decisions are taken. In order to assess the value of information, two settings are analyzed. Under the first setting, the manufacturer takes decisions under perfect information. To find the optimal decisions under perfect information, a stochastic model is introduced. Under the second setting, the manufacturer takes decisions under imperfect information. To obtain a solution for this problem, Partially Observable Markov Decision Process is employed. Under the second setting, we study two approaches. In the first approach, we introduce a nonlinear programming model to find the optimal decisions. In the second approach, a heuristic approach, constructed on optimal actions taken under perfect information is presented. We examine the value of information under different parameters by considering the policies under nonlinear programming model and heuristic approach. The profit gap between the two policies is investigated. The effect of Make-to-Order (MTO) and Make-to-Stock (MTS) schemes on the value of information is analyzed. Lastly, different lead time quotation schemes / accept-all, accept-reject and precise lead time / are compared to find under which quotation scheme value of information is highest.

abstract: Today's competitive markets force companies to constantly engage in the complex task of managing their demand. In make-to-order manufacturing or service systems, the demand of a product is shaped by price and lead times, where high price and lead time quotes ensure profitability for supplier, but discourage the customers from placing orders. Low price and lead times, on the other hand, generally result in high demand, but do not necessarily ensure profitability. The price and lead time quotation problem considers the trade-off between offering high and low prices and lead times. The recent practices in make-to- order manufacturing companies reveal the importance of dynamic quotation strategies, under which the prices and lead time quotes flexibly change depending on the status of the system. In this dissertation, the objective is to model a make-to-order manufacturing system and explore various aspects of dynamic quotation strategies such as the behavior of optimal price and lead time decisions, the impact of customer preferences on optimal decisions, the benefits of employing dynamic quotation in comparison to simpler quotation strategies, and the benefits of coordinating price and lead time decisions. I first consider a manufacturer that receives demand from spot purchasers (who are quoted dynamic price and lead times), as well as from contract customers who have agree- ments with the manufacturer with fixed price and lead time terms. I analyze how customer preferences affect the optimal price and lead time decisions, the benefits of dynamic quo- tation, and the optimal mix of spot purchaser and contract customers. These analyses necessitate the computation of expected tardiness of customer orders at the moment cus- tomer enters the system. Hence, in the second part of the dissertation, I develop method- ologies to compute the expected tardiness in multi-class priority queues. For the trivial single class case, a closed formulation is obtained. For the more complex multi-class case, numerical inverse Laplace transformation algorithms are developed. In the last part of the dissertation, I model a decentralized system with two components. Marketing department determines the price quotes with the objective of maximizing revenues, and manufacturing department determines the lead time quotes to minimize lateness costs. I discuss the ben- efits of coordinating price and lead time decisions, and develop an incentivization scheme to reduce the negative impacts of lack of coordination. / Dissertation/Thesis / Ph.D. Industrial Engineering 2012