Coordinated Scheduling of Customer Orders for Quick Response Reza Ahmadi, 1 Uttarayan Bagchi, 2 Thomas A. Roemer 3 1 Anderson School of Management, University of California at Los Angeles, Los Angeles, California 90095 2 Department of Management, CBA 4.202, The University of Texas, Austin, Texas 78712 3 Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142 Received 3 December 2002; revised 12 April 2005; accepted 12 April 2005 DOI 10.1002/nav.20092 Published online 13 June 2005 in Wiley InterScience (www.interscience.wiley.com). Abstract: The scheduling problem addressed in this paper concerns a manufacturer who produces a variety of product types and operates in a make-to-order environment. Each customer order consists of known quantities of the different product types, and must be delivered as a single shipment. Periodically the manufacturer schedules the accumulated and unscheduled customer orders. Instances of this problem occur across industries in manufacturing as well as in service environments. In this paper we show that the problem of minimizing the weighted sum of customer order delivery times is unary NP-hard. We characterize the optimal schedule, solve several special cases of the problem, derive tight lower bounds, and propose several heuristic solutions. We report the results of a set of computational experiments to evaluate the lower bounding procedures and the heuristics, and to determine optimal solutions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics 52: 493–512, 2005. Keywords: sequencing; customer orders; algorithms and complexity; bounding procedure 1. INTRODUCTION This paper discusses a sequencing problem that occurs in many manufacturing and service environments. Consider, for example, a product development team whose members independently develop modules for a number of different products. A product design is only completed once all modules have been designed. A natural performance crite- rion for the development team is the average completion time of all product designs, or, in the presence of ranked importance of the designs, the weighted average completion time. A team of accountants auditing distinct parts of dif- ferent companies is another example. The customer, the audited company, receives a final report only after all ac- countants have finished their work. Again, the (weighted) average completion time, that is, the time until the company receives the final report, is a crucial performance measure. In manufacturing, this problem arises in many assembly situations. Assembly can only proceed if all parts for as- sembly are available. Thus, completion time is largely de- termined by the time that the last component is manufac- tured. Under 0-inventory policies or mass customization schemes where each component is unique, the time until the customer receives the assembled product is then mainly determined by the manufacturing schedule of the compo- nents. Specifically, this research is motivated by a manufacturer that produces semifinished lenses and competes in the global market. The lenses are sold to professional lens finishing labs, and some large optometrist stores. The man- ufacturer produces three types of plastic lenses: CR-39, Polycarbonate, and Spectralite. The CR-39 is the industry standard for plastic lenses. The Polycarbonate lenses are made of higher index materials than CR-39, which give longer durability to this type of lens. The Spectralite lenses are made of higher index materials but do not require as much curing as the Polycarbonate lenses. Due to the nature of processing requirements, each type of plastic lens is produced on a dedicated production line. The manufacturer produces lenses based on confirmed customer orders. Each customer order consists of different quantities of the three lens types. Different parts of the customer order, after completion on the different production lines, are sent to the Correspondence to: T.A. Roemer (troemer@mit.edu); R. Ah- madi (rahmadi@anderson.ucla.edu); U. Bagchi (uttarayan.bagchi@ mccombs.utexas.edu) © 2005 Wiley Periodicals, Inc.