Technical Sessions – Monday July 11

MB-03 IFORS 2011 - Melbourne
� MB-03
Monday, 14:00-15:30
Meeting Room 102
Hybrid Metaheuristics
Stream: Meta-heuristics
Invited session
Chair: Celso Ribeiro, Department of Computer Science,
Universidade Federal Fluminense, Rua Bogari 70, 22471-340, Rio de
Janeiro, RJ, Brazil, celso@inf.puc-rio.br
Chair: Stefan Voss, Wirtschaftsinformatik/Information Systems,
University of Hamburg, Von-Melle-Park 5, 20146, Hamburg,
Germany, stefan.voss@uni-hamburg.de
1 - The Myopic Dynamic Programming Approach for the
Knapsack Problem with Time-window
Misato Okada, National Defense Academy, Computer Science
Dept., Hasirimizu, Yokosuka, Kanagawa, Japan,
em49034@nda.ac.jp, Seiji Kataoka
The knapsack problem called KPTW is as follows: each item has the consecutive
periods (time-window) in which we can take it, and the total amount of
weights in each period has to be within the capacity. We propose the myopic
dynamic programming that sees only expected states. It uses memory of limited
size, but can reach an almost optimal solution. It also gives non-decreasing
lower bounds anytime in the process. With effective upper bounds on them, a
considerable number of variables can be pegged. Besides, by deleting redundant
constraints, we succeed in diminishing KPTW to solvable size.
2 - Iterated Hybrid Metaheuristics for Solving Single-
Machine Total Weighted Tardiness Problems with
Sequence-Dependent Setup Times
Chun-Lung Chen, Department of Accounting Information,
Takming University of Science and Technology, Taiwan,
charleschen@takming.edu.tw
An iterated hybrid metaheuristic is proposed to solve the single-machine
scheduling problems with sequence-dependent setup times. The algorithm first
integrates the principles of the Variable Neighborhood Search and Tabu Search
to achieve a local optimal solution, and then a shaking procedure is developed
to perturb the best solution to obtain a new initial solution attempt to escape
the local optimal solution. To verify the proposed algorithm, computational
experiments were conducted on benchmark problem sets and the results show
the proposed algorithm outperforms several meta-heuristics.
3 - Restart Strategies for GRASP with Path-relinking
Heuristics
Celso Ribeiro, Department of Computer Science, Universidade
Federal Fluminense, Rua Bogari 70, 22471-340, Rio de Janeiro,
RJ, Brazil, celso@inf.puc-rio.br, Mauricio Resende
GRASP with path-relinking is a hybrid metaheuristic for combinatorial problems.
A restart strategy in GRASP with path-relinking is a set of iterations on
which the heuristic is restarted from scratch using a new seed for the random
number generator. Restart strategies have been shown to speed up stochastic
local search algorithms. We propose a restart strategy for GRASP with
path-relinking. We illustrate the speedup obtained with this restart strategy on
heuristics for the maximum cut problem, the maximum weighted satisfiability
problem, and the private virtual circuit routing problem.
� MB-04
Monday, 14:00-15:30
Meeting Room 103
Spare Parts Inventory Systems
Stream: Operations Management
Invited session
Chair: Scott Webster, Syracuse University, 13244, Syracuse, NY,
United States, stwebste@syr.edu
1 - A Spare Parts Provisioning Problem
12
Baris Balcioglu, Mechanical and Industrial Engineering,
University of Toronto, 5 King’s College Road, M5S 3G8,
Toronto, ON, Canada, baris@mie.utoronto.ca, Pedram Sahba,
Dragan Banjevic
We analyze a system of different fleets of machines where machines can fail
due to a single type of critical component. A certain number of critical components
are kept in a centralized inventory as spare parts with a shared inventory
serving all fleets and reserved inventories for each fleet. Failed components
are repaired in a single repair shop and the destination fleet can be chosen either
on an FCFS basis or by considering static or dynamic priority rules among
the fleets. Our numerical examples indicate that the best policy is a system
operating under the inventory rationing policy.
2 - A Finite Horizon Spare Parts Inventory Problem
Nesim Erkip, Industrial Engineering, Bilkent University, 06800,
Ankara, Turkey, nesim@bilkent.edu.tr
While considering the life-cycle of a spare part inventory problem, one usually
assumes that there are two main phases, followed by the final phase. The first
main phase is when the part is steadily used for assembly, and the second main
phase represents the periods when the part is no longer used as an input for
manufacturing, but has a stochastic demand as a spare part. The final phase, on
the other hand is usually represent by a single procurement. In this study, we
propose a heuristic that will consider the joint problem that reflects the second
main phase, with the final phase.
3 - Final Purchase and End-of-Life Acquisition Decisions
in Response to a Component Phase-Out Announcement
Scott Webster, Syracuse University, 13244, Syracuse, NY,
United States, stwebste@syr.edu, Dwayne Cole, Burak Kazaz
We consider a problem faced by a durable-goods manufacturer of a product
that is no longer manufactured but still under warranty. A supplier announces
that a component of the product will be phased out and specifies a deadline for
the final order. The manufacturer faces a two-stage decision problem: (1) the
size of the final order and, in the event that the final order is less than actual requirements,
(2) the design of a trade-in program for component harvesting. We
investigate how a firm’s trade-in policy, decisions, and profits are influenced by
industry and market characteristics.
� MB-05
Monday, 14:00-15:30
Meeting Room 104
Service Operation Management
Stream: Service Science and Sustainability
Invited session
Chair: Ming Chun Tsai, Chung Hua University, 30012, Hsinchu,
Taiwan, mctsai@chu.edu.tw
Chair: Shu-Ping Lin, Technology Management, Chung Hua
University, 707, Sec.2, WuFu Rd., 30012, Hsinchu, Taiwan,
splin@chu.edu.tw
1 - A Study of Inertia Type and Inertia Relational Model
Ming Chun Tsai, Chung Hua University, 30012, Hsinchu,
Taiwan, mctsai@chu.edu.tw, Ching-Chan Cheng
Inertia is characteristic of human nature. Service providers can then take advantage
of the inertia to keep up good relationships with their customers. Accordingly,
this study are, first, to explore the core variables of the inertias by
analyzing the dependencies among them through DEMATEL; second, to study
the main factors affecting the inertias so as to establish an inertia relationship
model. Finally, as a case in point, SEM will be utilized to empirically examine
the customer inertia relationship model of the fashion business to identify the
leading factors affecting its customer inertias.
2 - Adopting Quality Functional Deployment to Enhance
the Service Recovery Implementation
Yahui Chan, Technology Management Dept., Chung Hua
University, Hsinchu, Taiwan, silvia_219@yahoo.com.tw,
Shu-Ping Lin