Informs 2015

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INFORMS Philadelphia – 2015
400
WA79
79-Room 302, CC
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.,
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.
Wednesday, 11:00am - 12:30pm
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,
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,
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,
1 - Risk Measures of Machine Breakdowns in Job Shop Scheduling
Shu-dong Sun, Prof, Northwestern Polytechnical University,
No127 West Youyi RD, Xi’An, China,
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.
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,
, 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,
, 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,
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,
, 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.
WB03
03-Room 303, Marriott
Newsvendor Model and Extensions
Contributed Session
Chair: Layth Alwan, Associate Professor, University of Wisconsin-
Milwaukee, P.O. Box 742, Milwaukee, WI, 53201, United States of
America,
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,
, 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, , 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.
WA79