Technical Sessions – Monday July 11

HB-06 IFORS 2011 - Melbourne
2 - Exact Analysis of Divergent Systems with Time-Based
Shipment Consolidation and Compound Poisson Demand
Olof Stenius, Industrial Management & Logistics, Lund
University - Faculty of Engineering, Ole Römers väg 1, Box 118,
SE-221 00, Lund, Sweden, olle.stenius@iml.lth.se, Gönül
Karaarslan, Johan Marklund, Ton de Kok, Gudrun Kiesmüller
Sustainable management of VMI systems require integration of transportation
and inventory planning. In this context, a one warehouse multi-retailer system
with point-of-sales data, time-based shipment consolidation and compound
Poisson demand is studied. Exact costs for single- and multi-item systems are
derived, and optimization of shipment interval and reorder points is provided
both for systems with shortage cost and fill-rate constraints. This is done by
examining the warehouse backorder distribution for each retailer.
3 - Effect of Lead Time Information Sharing on the Performance
of Retailer in a Supply Chain: A Simulation
Study
Padmapriya Pugazhendhi, Department of Management Studies,
IIT Madras, Room no.453, Sarayu Hostel, IIT Madras, 600036,
Chennai, TamilNadu, India, priyap.cool@gmail.com, Arshinder
Kaur
Supply chain risks refer to the supply and demand uncertainty which results
in poor supply chain performance. An attempt has been made in this paper to
model the supply side risk that arises due to supplier’s lead time uncertainty in
the presence of uncertain customer demand in a single-supplier-single-retailer
supply chain. A MILP model has been proposed and through simulation exercise
the present work evaluates the benefit of sharing information on supplier
lead time in the form of improved fill rate and reduced total cost for the retailer.
4 - Innovative Dynamic Pricing Strategies under Strategic
Consumer Behavior
Yossi Aviv, Olin Business School, Washington University in
Saint Louis, Campus Box 1133, 1 Brookings Drive, 63130, Saint
Louis, MO, United States, aviv@wustl.edu
When implementing dynamic pricing, retailers must account for the fact that,
often, strategic customers may time their purchases in anticipation of future discounts.
Such strategic consumer behavior might lead to severe consequences
on the retailers’ revenues and profitability. In this talk, we will discuss some
ways in which sellers can adopt creative dynamic pricing schemes to optimally
price products in the face of strategic consumer behavior.
� HB-06
Thursday, 11:00-12:30
Meeting Room 105
Industrial Applications of Scheduling and
Routing II
Stream: Transportation
Invited session
Chair: Geir Hasle, Applied Mathematics, SINTEF ICT, P.O. Box 124
Blindern, NO-0314, Oslo, Norway, geir.hasle@sintef.no
1 - Optimising Line-Haul Distribution Networks Using a Vehicle
Routing Algorithm
Philip Kilby, NICTA, Australian National University, RSISE
Building 115, North Rd ANU, 0200, Canberra, ACT, Australia,
Philip.Kilby@nicta.com.au, Andrew Verden
In the usual formulation of the Vehicle Routing Problem, a set of routes is
calculated for a fleet of vehicles to deliver goods from depot(s) to a set of customers
at minimum cost. However, in distribution systems, goods are first taken
from a port or manufacturing centre, and delivered to the depots. This bulk
transport phase is called "line-haul". While the line-haul problem share some
common ground with the VRP, it is not usually solved using VRP solvers. In
this talk, we will describe how a VRP solver was used to solve a line-haul
distribution problem for an Australian food manufacturer.
2 - A Multi-trip Routing Problem with Time Window and
Meal Break
80
Suk Fung Ng, Institute of Transport and Logistics Studies,
University of Sydney, ITLS, C37, Faculty of Economics and
Business, 2006, Sydney, NSW, Australia,
suk.ng@sydney.edu.au, Daniel Oron, San Nah Sze
A multi-trip routing problem with time window and meal break consideration,
motivated by a real life application in in-flight catering, is studied. Loading
teams delivers packaged meals to aircraft within their transit time windows.
Due to limited truck capacity, loading teams have to serve aircraft in multiple
trips. An insertion and a two-stage heuristics are developed for the cases without
and with workforce synchronisation, respectively. The solutions provided
by the algorithms are shown to be effective and efficient compare with the one
provided by the company’s professional planner.
3 - Operation Control Strategies to Improve Transfers Between
High-Frequency Urban Rail Lines
Felipe Delgado, Transport and Logistics, Pontificia Universidad
Católica de Chile, 1, Chile, fadelgab@gmail.com, Juan Carlos
Muñoz, Nigel H.M. Wilson, Corey Wong
In high frequency transit systems that lack coordinated transfers, groups of
passengers could benefit from faster connections if selected departing vehicles
were held for short periods. To solve this problem, we propose a real-time
mathematical programming model for transfer’s coordination. The decision is
whether or not to hold a departing vehicle at the transfer station in order to allow
some, or all of the transferring passengers on an arriving vehicle to board
this one. An application from the single highest-volume transfer station in the
Boston subway network, Park Street, is presented.
4 - A Capacitated Clustering-based Method for Newspaper
Delivery Routing
Geir Hasle, Applied Mathematics, SINTEF ICT, P.O. Box 124
Blindern, NO-0314, Oslo, Norway, geir.hasle@sintef.no, Oddvar
Kloster, Morten Smedsrud
We present an efficient solver that produces clustered, balanced, and cost effective
routes for distribution in a given geographical area. Through cloud computing,
the optimization functionality is used by some 30 Norwegian, Swedish,
and Finnish newspaper distribution companies for solving Large-scale Node
Edge Arc Routing Problems (NEARP) with route duration, route balancing,
and route compactness constraints. First, we solve a capacitated clustering
problem. The corresponding NEARP solution is further optimized through a
combination of ILS and VND.
� HB-07
Thursday, 11:00-12:30
Meeting Room 106
Topics in Combinatorial Optimization III
Stream: Combinatorial Optimization
Invited session
Chair: Juan José Salazar González, Estadística e Investigación
Operativa, Universidad de La Laguna (Tenerife), Av. Astrofísico
Francisco Sánchez, s/n, Facultad de Matemáticas, 38271, La Laguna,
Tenerife, Spain, jjsalaza@ull.es
1 - Decomposition and Sensitivity Analysis Study for the
Multiple Scenario Max-min Knapsack Problem: the
Profit Variations
Abdelkader Sbihi, Information & Finance, Euromed
Management, Marseille, France, Domaine de Luminy, BP 921,
13288, Marseille cedex 9, France,
Abdelkader.Sbihi@euromed-management.com
We study a decomposition and profit variations sensitivity analysis for the Multiple
Scenario Max-Min Knapsack Problem which is a max-min combinatorial
optimization. The aim is to select the better scenario leading to the best outcome.
We present a decomposition strategy by considering a sequence of knapsack
problems, each related to a scenario and with a specific capacity. We study
the sensitivity analysis of the optimal solution to the profits variations by building
robust intervals bounding the variations. The obtained experiment results
demonstrated a high efficiency of our approach.
2 - Determining Clusters for Existence of Solutions for the
Optimal Stars Clustering Tree Problem
Michal Stern, Academic College of Tel-Aviv Yaffo, Rabenu
Yeruham St., 61083, Tel-Aviv, Israel, stern@mta.ac.il, Ron