Technical Sessions – Monday July 11

HD-02 IFORS 2011 - Melbourne
� HD-02
Thursday, 15:30-17:00
Meeting Room 101
Production Scheduling
Stream: Scheduling
Contributed session
Chair: Sergio Maturana, Ingenieria Industrial y de Sistemas, P.
Universidad Catolica de Chile, Casilla 306 Correo 22, Santiago,
Chile, smaturan@ing.puc.cl
1 - Metaheuristic Solution Approaches for the Open-pit
Mine Production Scheduling Problem with Grade Uncertainty
Amina Lamghari, Mining and Materials Engineering, McGill
University, Frank Dawson Adams, Rm 113, 3450 University
street, H3A 2A7, Montreal, Quebec, Canada,
amina.lamghari@mail.mcgill.ca, Roussos Dimitrakopoulos
We consider a stochastic version of the open-pit mine production scheduling
problem. In this problem, the mineral deposit is represented as a threedimensional
grid of blocks, and the metal content of the blocks is the source
of uncertainty. The problem can be formulated as a two-stage stochastic program
with recourse. We propose two metaheuristic solution approaches based
on tabu search and variable neighborhood search. Numerical results are provided
to indicate the efficiency of the proposed methods to generate very good
solutions in reasonable computational times.
2 - Operative Production Planning under Demand Uncertainty
in the Context of the Automotive Industry with
Rolling Horizons
Stefan Kloepfer, CIM, Heinz Nixdorf Institute, Fürstenallee 11,
33102, Paderborn, Germany, stefan.kloepfer@hni.upb.de,
Wilhelm Dangelmaier
In order to achieve efficient production planning, the subtasks of lotsizing,scheduling
and capacity assignment under demand uncertainty have to
be solved simultaneously because of their interdependencies. To cope with
this problem, we present a holistic 2-stage stochastic model with a time based
aggregation scheme that reduces complexity at small loss of accuracy by integrating
the concept of rolling horizons. Moreover,we show the benefit of using
a stochastic model and elaborate on an approach for deriving realistic scenario
sets in this context of long term customer-supplier relationships.
3 - Minimising the Cycles Traversed on a Unidirectional
Cyclical Picking Line
Jason Matthews, Department of Logistics, University of
Stellenbosch, South Africa, 14855054@sun.ac.za, Stephan
Visagie
A real life order pick operation making use of cyclical picking lines used by Pep
Stores Ltd, South Africa, is considered. Multiple pickers walk in a clockwise
direction around a conveyor belt picking from fixed bin locations. The problem
of sequencing orders for these pickers is discussed. A strong lower bound on
the number of cycles needed for a wave of picking is established. Results on a
dynamic solution approach to the real life problem are presented
4 - Integrating Planning and Scheduling Sawmill Operations
Sergio Maturana, Ingenieria Industrial y de Sistemas, P.
Universidad Catolica de Chile, Casilla 306 Correo 22, Santiago,
Chile, smaturan@ing.puc.cl, Mauricio Varas
A recurring problem faced by many firms is how to plan and schedule their
operations. Although both stages are required, frequently they are difficult to
integrate taking into account the uncertainty faced by the firm. An "optimal’
plan might result in a suboptimal schedule due to unforeseen changes. We
present a preliminary study on integrating planning and scheduling of operations
at a sawmill using an optimization model for the planning stage, and a
simple heuristic for the scheduling stage. Monte-Carlo simulation is used to
study the properties of the solutions generated by the approach.
98
� HD-03
Thursday, 15:30-17:00
Meeting Room 102
Travel Behaviour 3
Stream: Travel Behaviour
Invited session
Chair: John Rose, The University of Sydney, NSW 2006, Sydney,
Australia, JohnR@itls.usyd.edu.au
1 - Measuring the Impact of Individuals’ Perceptions on
their Transport Mode Choice
Aurélie Glerum, Transport and Mobility Laboratory, École
Polytechnique Fédérale de Lausanne (EPFL), Lausanne,
Switzerland, aurelie.glerum@epfl.ch, Bilge Atasoy, Michel
Bierlaire
This research aims at analyzing the impact of individuals’ perceptions on their
transport mode preferences through an integrated choice and latent variable
model. Here perceptions are measured through adjectives describing several
different transport modes. The adjectives were freely reported by respondents
of a survey conducted in low-density areas. They build a new type of data
consisting of words that can be classified according to a perception scale and
introduced in a discrete choice model as measurement equations of a latent
perception of a transport mode.
2 - Profiling Public Events from Mobility Data
Francisco Pereira, SMART/ITS, MIT, 77 Mass Ave. Room
1-249, 02139, Cambridge, MA, United States, camara@dei.uc.pt
This paper describes a methodology for identifying public home distributions in
planned special events. We analyze a massive dataset of localized cell-phone
records to infer crowd traces. A neural network model then predicts crowd
home distributions at the zipcode area level. Experiments based on 52 events
in the city of Boston show an RMSE of 4.89% in the prediction for high demand
areas. This work demonstrates the value of mobility data for the support
of travel demand management and ultimately to a more responsive city without
compromising critical issues such as privacy or security.
� HD-04
Thursday, 15:30-17:00
Meeting Room 103
Carbon Emissions and Supply Chains
Stream: Supply Chain Management
Invited session
Chair: Tarkan Tan, Industrial Engineering, Eindhoven University of
Technology, Den Dolech 2, Pav F-07, 5612AZ, Eindhoven,
Netherlands, t.tan@tue.nl
1 - Effect of Carbon Emission Regulations on Transport
Mode Selection in Supply Chains
Tarkan Tan, Industrial Engineering, Eindhoven University of
Technology, Den Dolech 2, Pav F-07, 5612AZ, Eindhoven,
Netherlands, t.tan@tue.nl, Kristel Hoen
We investigate the effect of two regulation mechanisms to drive down carbon
emissions on the transport mode selection decision: an emission cost and an
emission constraint. We use an accurate calculation method to determine the
carbon emissions and incorporate them explicitly in our model. Our results
show that introducing an emission cost for freight transport, e.g. via a market
mechanism such as cap-and-trade, will not result in large emission reductions.
2 - Carbon-optimal Supply Chains
Charles Corbett, UCLA Anderson School of Management, 110
westwood plaza, box 951481, 90095-1481, Los Angeles, CA,
United States, charles.corbett@anderson.ucla.edu, Felipe Caro,
Tarkan Tan, Rob Zuidwijk
In this paper we explore the differences between making a supply chain carbonneutral
by offsetting all emissions vs. making it carbon-optimal by inducing all
parties to invest appropriately in reducing GHG emissions. We examine conditions
under which first-best can and cannot be achieved, and examine various
decentralized outcomes.