2015 Informs Annual Meeting

WA79

INFORMS Philadelphia – 2015

WA79 79-Room 302, CC

2 - A Computational Study of the Two-Machine No-Wait Flow Shop Problem Subject to Unequal Release Dates and Non-Availability Constraints Mohamed Labidi, Assistant Professor, King Saud University, Industrial Engineering Dept., Riyadh, Saudi Arabia, mlabidi@ksu.edu.sa, Anis Kooli, Talel Ladhari We consider the problem of scheduling a set of jobs subject to unequal release dates on a two-machine flow shop where the no-wait and non-availability constraints are considered so as to minimize the makespan. We propose several new lower bounds that are embedded within a branch-and-bound algorithm. Computational results show that our procedure outperforms state-of-the art exact method. 3 - Heuristic Approach for an Unrelated Parallel Machine Scheduling Problem with Ready Times, Due Dates Bin Li, University of Arkansas, 4110 Bell Engineering Center, Fayetteville, AR, 72701, United States of America, binli@email.uark.edu, Ashlea Milburn We present a scheduling problem with unrelated parallel machines, ready times, due dates, limited machine availability and job splitting. The objective is to minimize the total job processing time. This research is motivated by a real warehouse labor scheduling problem. The effectiveness of exact and heuristic methods in developing solutions to a large variety of test instances are compared in a computational study. Results are presented. 4 - Singe-machine Preemptive Scheduling of Equal-processing-time Jobs Vadim Timkovski, Keiser University, Fort Lauderdale, FL, United States of America, vtimkovski@keiseruniversity.edu We show that the problem of minimizing the total weighted tardiness with different release dates can be solved in pseudo-polynomial time. 5 - Integrated Production and Shipping Scheduling for A Single Manufacturer and Multiple Customers Fangzhou Sun, Virginia Tech, 250 Durham Hall, 1145 Perry Street, Blacksburg, VA, 24060, United States of America, fangzhou@vt.edu, Subhash C. Sarin, Yuqiang Wang We investigate a supply chain scheduling problem consisting of a single manufacturer and multiple customers, which integrates the production and shipping decisions so as to minimize the weighted sum of costs incurred due to shipping and number of tardy orders. We develop a heuristic and an optimum- seeking algorithm both of which exploit the structural properties of the problem. Computational results reveal efficacy of the proposed methods and significant benefits that accrue from integration. Chair: Layth Alwan, Associate Professor, University of Wisconsin- Milwaukee, P.O. Box 742, Milwaukee, WI, 53201, United States of America, alwan@uwm.edu 1 - Can Server Behavior and Service System Design Outweigh the Benefits of Pooling? Marilyn Lucas, University of Vermont, 55 Colchester Ave., Burlington, VT, 05405, United States of America, mlucas@bsad.uvm.edu, Hung Do, David Novak, Masha Shunko It is widely accepted that multi-server single-queue (SQ) systems outperform multi-server parallel-queue (PQ) systems due to the pooling effect. We investigate the impact of two server behaviors - social loafing and workload-dependent speedup - and one physical factor - walking time - on the performance of SQ and PQ systems. 2 - Either Forecast Optimally or Opt Out: Newsvendor Perspective Layth Alwan, Associate Professor, University of Wisconsin- Milwaukee, P.O. Box 742, Milwaukee, WI, 53201, United States of America, alwan@uwm.edu, Xiaohang Yue The newsvendor model assumes IID demand. In application, demand can exhibit serial correlation. The natural adaptation is to develop a forecast-based implementation. For stationary processes, such as an AR(1), an implementation based on an MSE optimal forecasting method always provides long-term savings. However, under certain conditions, commonly implemented smoothing methods fail to provide long-term benefits. As a result, it best to ignore the correlation and opt out of forecasting. WB03 03-Room 303, Marriott Newsvendor Model and Extensions Contributed Session

Software Demonstration Cluster: Software Demonstrations Invited Session 1 - Optimization Direct, Inc. – Solving Large Scale Optimization Problems using CPLEX Optimization Studio Robert Ashford, Optimization Direct, Inc., Alkis Vazacopoulos Recent advancements in Linear and Mixed Programing give us the capability to solve larger Optimization Problems. CPLEX Optimization Studio solves large-scale optimization problems and enables better business decisions and resulting financial benefits in areas such as supply chain management, operations, healthcare, retail, transportation, logistics and asset management. In this tutorial using CPLEX Optimization Studio we will discuss modeling practices, case studies and demonstrate good practices for solving Hard Optimization Problems. We will also discuss recent CPLEX performance improvements and recently added features. 2 - Introducing New Release 5.0 of the MPL Modeling System and the OptiMax Component Library Bjarni Kristjansson, Maximal Software Inc., 2111 Wilson Boulevard, Suite 700, Arlington, VA., bjarni@maximalsoftware.com, Maximal Software is introducing a new major release 5.0 of the MPL Modeling System, which represents a major milestone for MPL. We will be demonstrating the many new features and enhancements of MPL, including new directory structure, redesigned documentation, new solver updates, Reverse Hessian for nonlinear models, and enhanced Stochastic support. Major updates for the MPL OptiMax Library and the MPL Callable Library, include also new callbacks, new exception handlers, and enhanced multi-threaded support. WB01 01-Room 301, Marriott MAS Tutorial: A Logistics Planning System for Military Contingency Missions Sponsor: Military Applications Sponsored Session Chair: Greg Parlier, Past President, MAS of INFORMS, 255 Avian Lane, Madison, AL, 35758, United States of America, gparlier@knology.net 1 - A Logistics Planning System for Military Contingency Missions Matthew B. Rogers, U.S. Army / N.C. State University, 121 E. Cedar Ave, Wake Forest, NC, 27587, United States of America, mbroger2@ncsu.edu, Greg Parlier, Russell King, Brandon Mcconnell, Kristin Thoney-barletta, Thom Hodgson, Michael Kay Logistical considerations are a critical part of mission planning for contingency operations. A form of (near real-time) adaptive discrete event simulation is used to identify requirements for a logistic system during contingency mission planning. Mission-based forecasting is used to generate sustainment demand for the simulation. Network performance is used to modify interactively the logistic network until the contingency mission can be properly supported. WB02 02-Room 302, Marriott Scheduling II Contributed Session Chair: Vadim Timkovski, Keiser University, Fort Lauderdale, FL, United States of American, vtimkovski@keiseruniversity.edu 1 - Risk Measures of Machine Breakdowns in Job Shop Scheduling Shu-dong Sun, Prof, Northwestern Polytechnical University, No127 West Youyi RD, Xi’An, China, sdsun@nwpu.edu.cn, Zhigao Wu A mathematical measure for the risk of job shop scheduling with random machine breakdowns is presented. However, the mathematical measure is too hard to implement, a simulation-based and a calculation-based approximate measures are put forward. The performance of the two approximate measures is studied. Experiment results show that the calculation–based risk measure is more time saving than the simulation-based risk measure while the performance of the two measures are nearly the same. Wednesday, 11:00am - 12:30pm

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