Uday S. Karmarkar

Competition and Structure in Serial Supply Chains with Deterministic Demand

Supply chains often consist of several tiers, with different numbers of firms competing at each tier. A major determinant of the structure of supply chains is the cost structure associated with the underlying manufacturing process. In this paper, we examine the impact of fixed and variable costs on the structure and competitiveness of supply chains with a serial structure and price-sensitive linear deterministic demand. The entry stage is modeled as a simultaneous game, where the players take the outcomes of the subsequent post-entry Cournot competition into account in making their entry decisions. We derive expressions for prices and production quantities as functions of the number of entrants at each tier of a multitier chain. We characterize viability and stability of supply-chain structures and show, using lattice arguments, that there is always an equilibrium structure in pure strategies in the entry game. Finally, we examine the effects of vertical integration in the two-tier case. Altogether, the paper provides a framework for comparing a variety of supply-chain structures and for studying how they are affected by cost structures and by the number of entrants throughout the chain.

The Deterministic Dynamic Product Cycling Problem

Certain manufacturing situations involve a small number of items produced sequentially on the same facility with high changeover cost. Production schedules are characterized by long runs, and individual items are produced infrequently. At the same time, seasonal demand patterns require that the items be maintained in inventory in the right mix. This paper presents alternative formulations of this problem. It uses a Lagrangean relaxation approach to decouple the problem and provide lower bounds used in a branch and bound algorithm. Some experimental computations on small problems are reported.

Lotsizing in multi-item multi-machine job shops

Abstract A great many manufacturing facilities can be described as closed job shops which process multiple items through multiple work centers for stock or for assembly. The performance of these shops is strongly dependent on the batching policies employed for work in the shop. In particular, waiting time in queue and total manufacturing lead time for batches are functions of lotsizes. In turn these affect work-in-process costs, safety stock requirements, schedule performance and part coordination for assembly. The relationship between lot-sizing and shop performance is represented using a queueing network model which is then embedded in an optimization routine that searches for optimal lot sizes.

Service markets and competition

Abstract The production and delivery of services differ from manufacturing in ways which have a significant impact on the nature of market competition. Contracts for manufactured goods are centered around a clearly defined junction between production and use, made possible by the properties of tangibility and portability of tangible goods, at which point responsibility for use, operation and consumption of the product is transferred from producer to customer, along with ownership. Service operations, by contrast, involve a lack of inventories and portability, customer contact, joint production, customer-specific inputs, and intangibility in varying degrees. Moreover, service operations are either entirely post contractual or interlinked with the contracting process. As a result, the very nature of service markets and contracting depends on the characteristics of the service operation. While the operational consequences of service characteristics have been explored quite widely, there is less understanding of the special features of service competition and its implications for service strategy. We provide a framework for describing, analyzing and explaining service competition and review some old and new models which address the special features of service markets.

Design and operation of an order-consolidation warehouse: Models and application

Abstract A warehouse is a service facility, often comprising the only view that customers actually have of a manufacturing firm. The management of this facility has significant leverage over order leadtimes and fill-rate reliability. As with other service facilities, system design and operation are decision problems that are closely interlinked. In this paper we describe and model in general terms the composite design and operating problems for a typical order-consolidation warehouse. These problems include warehouse layout, equipment and technology selection, item location, zoning, picker routing, pick list generation and order batching. The complexity of the overall problem mandates developing a new multi-stage hierarchical decision approach. Our hierarchical approach utilizes a sequence of coordinated mathematical models to evaluate the major economic tradeoffs and to prune the decision space to a few superior alternatives. Detailed simulation employing actual warehousing data is then used for validation and fine tuning of the resulting design and operating policies. We describe the application of this analytical approach to an automotive spare-parts distribution centre. The case study demonstrates substantial savings in operating costs and highlights several generic management tradeoffs.

Chapter 6 Manufacturing lead times, order release and capacity loading

Manufacturing lead times are a critical measure of manufacturing performance that have not received a great deal of attention in the literature. Lead times are affected by many factors including capacity, loading, batching and scheduling, and themselves affect many aspects of costs, and control. The interaction between lead times and order release mechanisms is discussed and models relating them are described. In addition, models incorporating lead times in capacity planning and design decisions are also surveyed and some directions for research are discussed.

Competitive location on a network

In this paper we study the problem of locating facilities on a network in the presence of competition. Customers at each node in the network choose from the available facilities so as to minimize the distance traveled. The problem is to find a set of facilities that is stable in the sense that each facility is economically viable and no competitor can successfully open any facilities. We define several versions of stability and establish certain relationships between them. We then present integer programming formulations that identify stable sets, and describe an enumeration algorithm for constructing a profit-maximizing stable set.

Batching Policy in Kanban systems

Abstract Kanban systems differ from traditional inventory-oriented pull systems in that they permit consideration of the interaction between production lead time and inventory levels. In this paper, the effect of batch sizing policy on production lead time—and hence on inventory levels and cell performance—is studied. Both single- and dual-card Kanban cells and two-stage Kanban systems are modeled as Markovian processes, and the effect of batch sizing on expected inventory and back order costs is studied. It is further shown that batching policy has a significant impact on costs. The effect of varying the card count in the cell is also examined. The parameters provide substantial control over the performance of Kanban systems.

The dynamic lot-sizing problem with startup and reservation costs

Dynamic lot-sizing models often assume that a production system incurs a fixed cost in each period that production is positive. In this paper, we consider a model with a startup cost incurred for switching on the production facility and a separate reservation cost charged for keeping the facility on whether or not it is used for production. Computationally, this problem is as hard as the usual model; the general capacitated case is NP-hard. We present a dynamic programming algorithm for the uncapacitated case, and a branch-and-bound approach using Lagrangian relaxation for the capacitated problem. We report computational experience on both the quality of the bounds employed and the effectiveness of the algorithm.

Contracting for Collaborative Services

In this paper, we analyze the contracting issues that arise in collaborative services, such as consulting, financial planning, and information technology outsourcing. In particular, we investigate how the choice of contract type---among fixed-fee, time-and-materials, and performance-based contracts---is driven by the service environment characteristics. We find that fixed-fee contracts contingent on performance are preferred when the service output is more sensitive to the vendors effort, that time-and-materials contracts are optimal when the output is more sensitive to the buyers effort, and that performance-based contracts dominate when the output is equally sensitive to both the buyers and the vendors inputs. We also discuss how the performance of these contracts is affected with output uncertainty, process improvement opportunities, and the involvement of multiple buyers and vendors in the joint-production process. Our model highlights the trade-offs underlying the choice of contracts in a collaborative service environment and identifies service process design changes that improve contract efficiency.