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Douglas J. Blocher - Indiana University, Kelley School of Business. Bloomington, IN, US

Douglas J. Blocher Douglas J. Blocher

Professor of Operations and Decision Technologies | Indiana University, Kelley School of Business

Bloomington, IN, UNITED STATES

Professor Blocher's research interests include customer order scheduling, changeover scheduling and supply chain management.

Secondary Titles (1)

  • Arthur M. Weimer Faculty Fellow



Douglas J. Blocher Publication



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Industry Expertise (2)



Areas of Expertise (4)

Customer Order Scheduling

Changeover Scheduling

Supply Chain Management

Lead Time / Cycle Time Reduction

Accomplishments (4)

Excellence Recognition Award (professional)

Kelley School of Business at Indiana University

Research Excellence Award (professional)

Kelley School of Business at Indiana University

MBA Teaching Excellence Award (professional)

Kelley School of Business at Indiana University

Named Outstanding Faculty (professional)

Business Week

Education (3)

Purdue University: Ph.D., Operations Management 1990

Purdue University: M.S., Operations Management 1983

Purdue University: B.S., Operations Management 1980

Articles (5)

Optimal Single Machine Scheduling of Products with Components and Changeover Cost

European Journal of Operational Research

2014 We consider the problem of scheduling products with components on a single machine, where changeovers incur fixed costs. The objective is to minimize the weighted sum of total flow time and changeover cost. We provide properties of optimal solutions and develop an explicit characterization of optimal sequences, while showing that this characterization has recurrent properties. Our structural results have interesting implications for practitioners, primarily that the structure of optimal sequences is robust to changes in demand.

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An Efficient Network-based Formulation for Sequence Dependent Setup Scheduling on Parallel Identical Machines

Mathematical and Computer Modelling

2013 This paper compares the efficacy of a newly developed network-based mixed-integer programming (MIP) formulation with three existing formulations for the sequence dependent setup scheduling problem with earliness/tardiness penalties. This research shows that the new model is more efficient in terms of computation time for larger multi-machine problems than the existing formulations of these problems. The mixed-integer nature of the formulation allows companies to solve this class of problems with any one of many commonly available integer programming software packages. The presented MIP formulation provides a unique and useful method of conceptualizing and modeling a practical, yet difficult, problem within industry.

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Value of Sharing Production Yield Information in a Serial Supply Chain

Production and Operations Management

2008 New developments in corporate information technology such as enterprise resource planning systems have significantly increased the flow of information among members of supply chains. However, the benefits of sharing information can vary depending on the supply chain structure and its operational characteristics. Most of the existing research has studied the impact of sharing downstream information (e.g., a manufacturer sharing information with its suppliers). We evaluate the benefits of sharing upstream yield information (e.g., a supplier sharing information with the manufacturer) in a two-stage serial supply chain in which the supplier has multiple internal processes and is faced with uncertain output due to yield losses. We are interested in determining when the sharing of the supplier's information is most beneficial to the manufacturer. After proposing an order-up-to type heuristic policy, we perform a detailed computational study and observe that this information is most beneficial when the supplier's yield variance is high and when end-customer demand variance is low. We also find that the manufacturer's backorder-to-holding cost ratio has little, if any, impact on the usefulness of information.

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Minimizing Customer Order Lead - Time in a Two - Stage Assembly Supply Chain

Annals of Operations Research

2008 Coordination across different process stages of the supply chain is becoming more common as the information needed for this coordination is easier to obtain and share. With the availability of this information, managers are beginning to recognize that there can be benefits to scheduling processes in a coordinated fashion. Thus, finding good schedules for the entire supply chain has added importance to today’s managers. Coordination of the material as it moves from one stage to the next should lead to improved customer order lead-time performance for the whole chain and thus better customer service overall. We look at a two-stage assembly supply chain with the objective of minimizing the average customer order lead-time. Minimizing lead-time is becoming increasingly important as customers demand quicker response. But beyond this better customer service objective, minimizing lead-time is consistent with keeping inventory costs low. We introduce a number of properties of optimal solutions, results for special problem cases, and a series of lower bounds. We also provide a number of intuitive heuristics for coordinated supply chain scheduling and test them to determine their effectiveness.

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Service and Cost Benefits through Clicks-and-Mortar Integration, Implications for the Centralization Decentralization Debate

European Journal of Operational Research

2007 Traditional “Brick-and-Mortar” operations face the challenge of adapting to a new set of competitive rules made necessary by consumers who want the option of ordering electronically via the Internet. To satisfy these customers, firms must develop strategies that integrate their standard retail in-store channel with this relatively new on-line channel. Therefore, this research is designed to provide insights into supply chain inventory management strategies relevant to “Clicks-and-Mortar” firms trying to satisfy both on-line and in-store sales. Specifically, this work considers the total cost implications of various inventory allocation strategies while maintaining target customer service levels. Analysis focuses on the development of models capable of handling new operating strategies made possible by electronic commerce. The implications of inventory risk pooling are considered in depth, revealing the existence of characteristics that determine whether completely centralized or decentralized policies are preferable.

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