Coping with production time variability via dynamic lead-time quotation

In this paper, we propose two dynamic lead-time quotation policies in an M/GI/1 type make-to-stock queueing system serving lead-time sensitive customers with a single type of product. Incorporating non-exponential service times in an exact method for make-to-stock queues is usually deemed difficult. Our analysis of the proposed policies is exact and requires the numerical inversion of the Laplace transform of the sojourn time of an order to be placed. The first policy assures that the long-run probability of delivering the product within the quoted lead-time is the same for all backlogged customers. The second policy is a refinement of the first which improves the profitability if customers are oversensitive to even short delays in delivery. Numerical results show that both policies perform close to the optimal policy that was characterized only for exponential service times. The new insight gained is that the worsening impact of the production time variability, which is felt significantly in systems accepting all customers by quoting zero lead times, decreases when dynamic lead-time quotation policies are employed

Order Acceptance and Scheduling: A Taxonomy and Review

Over the past 20 years, the topic of order acceptance has attracted considerable attention from those who study scheduling and those who practice it. In a firm that strives to align its functions so that profit is maximized, the coordination of capacity with demand may require that business sometimes be turned away. In particular, there is a trade-off between the revenue brought in by a particular order, and all of its associated costs of processing. The present study focuses on the body of research that approaches this trade-off by considering two decisions: which orders to accept for processing, and how to schedule them. This paper presents a taxonomy and a review of this literature, catalogs its contributions and suggests opportunities for future research in this area

Convexity Properties and Comparative Statics for M/M/S Queues with Balking and Reneging

We use sample path arguments to derive convexity properties of an M/M/S queue with impatient customers that balk and renege. First, assuming that the balking probability and reneging rate are increasing and concave in the total number of customers in the system (head-count), we prove that the expected head-count is convex decreasing in the capacity (service rate). Second, with linear reneging and balking, we show that the expected lost sales rate is convex decreasing in the capacity. Finally, we employ a sample-path sub-modularity approach to comparative statics. That is, we employ sample path arguments to show how the optimal capacity changes as we vary the parameters of customer demand and impatience. We find that the optimal capacity increases in the demand rate and decreases with the balking probability, but is not monotone in the reneging rate. This means, surprisingly, that failure to account for customersâ reneging may result in over-investment in capacity. Finally, we show that a seemingly minor change in system structure, customer commitment during service, produces qualitatively different convexity properties and comparative statics.Operations Management Working Papers Serie

Due date quotation in make-to-order systems with lead time sensitive customers

Due date management is a central issue when production is triggered by customer orders. In a wide range of industries, especially if either craftsmanship is necessary or small scale project management is employed, quoting short but still attainable due dates and sustaining the highest return for the company in the long run provides an important competitive edge. In this study, we consider a single stage make-toorder manufacturing system, where customers are quoted hundred percent reliable due dates, immediately after they arrive. Lead time sensitive customers are offered price discounts in return for due dates further out. Still, quoted lead times cannot be arbitrarily long, and strict upper bounds are imposed on these depending on the type of the customer order. The scheduler does not have any information about the future arrivals in terms of their type and timing, and s/he needs to make decisions in an online setting without prior information about the arrival process or the attributes. In this thesis, a framework which evaluates the potential decisions for each order in conjunction with the current temporary production schedule is introduced. Using this framework, a group of algorithms is developed which aim to maximize the long term profit per unit time by estimating the future implications of accepting an order with a certain due date. Computational results demonstrate that under mild congestion and relatively frequent arrival of high-margin orders, this group of algorithms outperform first-come-first-served (FCFS) order selection and sequencing approach which is typical in many contexts

Revenue Management for Make-to-Order and Make-to-Stock Systems

With the success of Revenue Management (RM) techniques over the past three decades in various segments of the service industry, many manufacturing firms have started exploring innovative RM technologies to improve their profits. This dissertation studies RM for make-to-order (MTO) and make-to-stock (MTS) systems. We start with a problem faced by a MTO firm that has the ability to reject or accept the order and set prices and lead-times to influence demands. The firm is confronted with the problem to decide, which orders to accept or reject and trade-off the price, lead-time and potential for increased demand against capacity constraints, in order to maximize the total profits in a finite planning horizon with deterministic demands. We develop a mathematical model for this problem. Through numerical analysis, we present insights regarding the benefits of price customization and lead-time flexibilities in various demand scenarios. However, the demands of MTO firms are always hard to be predicted in most situations. We further study the above problem under the stochastic demands, with the objective to maximize the long-run average profit. We model the problem as a Semi-Markov Decision Problem (SMDP) and develop a reinforcement learning (RL) algorithm-Q-learning algorithm (QLA), in which a decision agent is assigned to the machine and improves the accuracy of its action-selection decisions via a “learning process. Numerical experiment shows the superior performance of the QLA. Finally, we consider a problem in a MTS production system consists of a single machine in which the demands and the processing times for N types of products are random. The problem is to decide when, what, and how much to produce so that the long-run average profit. We develop a mathematical model and propose two RL algorithms for real-time decision-making. Specifically, one is a Q-learning algorithm for Semi-Markov decision process (QLS) and another is a Q-learning algorithm with a learning-improvement heuristic (QLIH) to further improve the performance of QLS. We compare the performance of QLS and QLIH with a benchmarking Brownian policy and the first-come-first-serve policy. The numerical results show that QLIH outperforms QLS and both benchmarking policies

Robust order promising

This dissertation deals with the development of a planning approach for supporting robust order promising. A high level of reliability from the customer’s and the company’s point of view (i.e. planning robustness and solution robustness) is to be achieved despite occurring uncertainty. In the literature, capable-to-promise (CTP) approaches are suggested to determine answers to customer inquiries taking into ac-count resource availability. Thereby, attempts are made to cover order- and resource-related uncertainty by means of robustness-generating measures. However, interactions between these measures as well as customer responses to proposed order specifications are not adequately taken into account. In order to cope with these issues, a hierarchical procedure for analyzing and coordinating robustness-generating measures is developed in this cumulative dissertation. In accordance with the operative character of order promising, the first two papers deal with the development of a CTP model which considers customer behavior as well as established robustness-generating measures. Due to the complexity of identified measure interactions, coor-dinating the robustness-generating measures with respect to profitability, as well as planning robustness and solution robustness is inevitable. Thus, in the third paper, parameter values of the measures are coordinated by means of a statistically-founded procedure and a limited multi-criteria search. The test results finally reveal that the developed procedure leads to highly efficient solutions

The Nature and Change of Bonds in Industrial Business Relationships

A focus on cooperative industrial business relationships has become increasingly important in studies of industrial relationships. If the relationships between companies are strong it is usually a sign that companies will cooperate for a longer time and that may affect companies’ competitive and financial strength positively. As a result the bonds between companies become more important. This is due to the fact that bonds are building blocks of relationships and thus affect the stability in the cooperation between companies. Bond strength affect relationship strength. A framework regarding how bonds develop and change in an industrial business relationship has been developed in the study. Episodes affect the bonds in the relationship strengthening or weakening the bonds in the relationship or preserving status quo. Routine or critical episodes may lead to the strengthening or weakening of bonds as well as the preservation of status quo. The method used for analyzing bond strength trying to grasp the nature and change of bonds was invented by systematically following the elements of the definitions of bonds. A system with tables was drawn up in order to find out if the bond was weak, of medium strength or strong. Bonds are important regulators of industrial business relationships. By influencing the bonds one may have possibilities to strengthen or weaken the business relationship. Strengthen the business relationship in order to increase business and revenue and weaken the relationship in order to terminate business where the revenue is low or where there may be other problems in the relationship. By measuring the strength of different bonds it can be possible to strengthen weak bonds in order to strengthen the relationship. By using bond management it is possible to strategically strengthen or weaken the bonds between the cooperating companies in order to strengthen the cooperation and tie the customer or supplier to the company or weaken the cooperation in order to terminate the relationship. The instrument for the management of bonds is to use the created bond audit in order to know which bonds resources should be focused on in order to increase or decrease their strength