Technical Sessions – Monday July 11
Technical Sessions – Monday July 11
Technical Sessions – Monday July 11
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HC-19 IFORS 20<strong>11</strong> - Melbourne<br />
� HC-19<br />
Thursday, 13:30-15:00<br />
Meeting Room 216<br />
Discrete and Global Optimization with<br />
Applications<br />
Stream: Discrete and Global Optimization<br />
Invited session<br />
Chair: Chi-Kong Ng, Systems Engineering & Engineering<br />
Management, The Chinese University of Hong Kong, Shatin, N.T,<br />
Hong Kong, ckng@se.cuhk.edu.hk<br />
Chair: Xiaoling Sun, School of Management, Fudan University, 670<br />
Guoshun Road, 200433, Shanghai, China, xls@fudan.edu.cn<br />
1 - Disaggregation and Dimension Reduction Methods in<br />
Solving Diophantine Equations<br />
Duan Li, Systems Engineering & Engineering Management<br />
Dept., The Chinese University of Hong Kong, Shatin, NT, Hong<br />
Kong, dli@se.cuhk.edu.hk, Bojun Lu, Baiyi Wu, Jianjun Gao<br />
0-1 Diophantine equations arise naturally in both real applications and theoretical<br />
studies. We investigate disaggregation and dimension reduction schemes<br />
in this study and present numerical comparison results with CPLEX.<br />
2 - Heuristics for Parallel Machine Scheduling with Batch<br />
Delivery Consideration<br />
Zhaohui Liu, Mathematics, East China University of Science and<br />
Technology, 200237, Shanghai, China, zhliu@ecust.edu.cn,<br />
Leiyang Wang<br />
Consider the parallel machine scheduling problem in which the finished jobs<br />
need to be delivered to a customer in batches by a single vehicle. The goal<br />
is to minimize the makespan. We distinguish two types of batching strategies.<br />
The strategy of Type 1 permits the jobs processed on different machines<br />
to compose a delivery batch; however, the strategy of Type 2 assumes that<br />
only the jobs processed on the same machine can compose a batch. For both<br />
types of the $m$-machine case, we propose 2-1/m-approximation algorithms<br />
respectively. For both types of the two-machine case, we obtain two improved<br />
4/3-approximation algorithms.<br />
3 - A Dynamic Programming Method for Separable<br />
Quadratic Integer Programming<br />
Jun Wang, Management Science & Engineering, Qingdao<br />
University, No. 308, Ningxia Road, 266071, Qingdao,<br />
Shandong, China, jwang@qdu.edu.cn, Duan Li, Qing Xu<br />
A dynamic programming method is proposed for solving nonlinear integer programming<br />
problem with separable quadratic objective function and separable<br />
convex quadratic constraints. To mitigate the curse of dimensionality in dynamic<br />
programming, the surrogate constraint formulation is used as a platform<br />
for powerful utilization of dynamic programming. In this paper, by investigating<br />
the contour of objective function, the feasible region constrated by the convex<br />
quadratic functions and their relationship in domain space, we find the condition<br />
under which zero duality gap is attained and propose a domain-cutting<br />
scheme to reduce the duality gap successively and eventually eliminate it.<br />
4 - A Modified Test-Problem Generator for Unconstrained<br />
Global Optimization<br />
Chi-Kong Ng, Systems Engineering & Engineering<br />
Management, The Chinese University of Hong Kong, Shatin,<br />
N.T, Hong Kong, ckng@se.cuhk.edu.hk, Duan Li<br />
A software for benchmarking unconstrained global optimization algorithms is<br />
developed. By combining n sophisticated univariate problems and applying linear<br />
transformation of variables, a class of inseparable test-problems with 2**n<br />
local minima is obtained. The generator, and a standard set of 300 test problems<br />
with 10 different sizes and 3 difficulty levels for MATLAB and GAMS<br />
are produced, and are available for download. Computational experiments have<br />
demonstrated the stability of the generating process and the controllability of<br />
assigning the difficulty level to the test problems.<br />
96<br />
� HC-20<br />
Thursday, 13:30-15:00<br />
Meeting Room 217<br />
Building Bridges between OR and Strategy<br />
Stream: OR and Strategy<br />
Invited session<br />
Chair: Martin Kunc, Warwick Business School, University of<br />
Warwick, Office E0.10, WBS Social Studies Building, CV4 7AL,<br />
Coventry, United Kingdom, martin.kunc@wbs.ac.uk<br />
1 - System Dynamics and Innovation: A Complex Problem<br />
with Multiple Levels of Analysis<br />
Martin Kunc, Warwick Business School, University of Warwick,<br />
Office E0.10, WBS Social Studies Building, CV4 7AL,<br />
Coventry, United Kingdom, martin.kunc@wbs.ac.uk<br />
System Dynamicists analyze innovation processes using two concepts: feedback<br />
processes and stock and flows. Feedback processes usually represent innovation<br />
processes comprising industry, organization and process levels. System<br />
dynamicists represented innovation processes differently using stock and<br />
flows. Practitioners have followed system hierarchical principles.<br />
2 - Defence Capability Prioritisation — A Systematic Approach<br />
Thitima Pitinanondha, Defence Science and Technology<br />
Organisation, Australian Department of Defence, F4-GF-029, 24<br />
Fairbairn Avenue, Defence Establishment Fairbairn, 2600,<br />
Canberra, ACT, Australia,<br />
thitima.pitinanondha@defence.gov.au, Andrea Hadley<br />
In Defence capability planning, prioritisation has increasingly become an important<br />
consideration for decision-makers who have to decide on the best<br />
fiscally-constrained investment strategy to deliver an appropriate set of capabilities.<br />
A number of techniques have been applied to different capability context<br />
levels to help in prioritising the Defence capability portfolio. There is a<br />
need for a systematic approach to select appropriate prioritisation techniques<br />
to assist decision-makers to achieve their expected outcomes and ensure transparency<br />
and accountability in the decision- making process. This paper describes<br />
a systematic framework developed to assist in the selection of agreed<br />
and appropriate prioritisation techniques.<br />
3 - Good Governance: A Strategy for Economic Growth in<br />
Africa<br />
Moses Dowart, Department of Applied Mathematics, National<br />
University of Science and Technology (NUST), 8327 Unit K<br />
Seke Chitungwiza Harare Zimbabwe, 263, Harare, Zimbabwe,<br />
mdowart@gmail.com<br />
Africa, a continent endowed with immense natural and human resources as<br />
well as great cultural, ecological and economic diversity, remained underdeveloped.<br />
Most African nations suffer from deep poverty and underdevelopment.<br />
Numerous development strategies have failed to yield the expected results.<br />
Although some believe that the continent is doomed to perpetual poverty<br />
and economic slavery, Africa has immense potential. The paper reveals that<br />
substantial resource endowment generally has a slowing effect on economic<br />
development, but Natural resource richness with good governance promotes<br />
economic growth.<br />
� HC-21<br />
Thursday, 13:30-15:00<br />
Meeting Room 218<br />
Sustainable Logistics<br />
Stream: OR and Real Implementation<br />
Invited session<br />
Chair: Belarmino Adenso-Diaz, Engineering School at Gijon,<br />
Universidad de Oviedo, Campus de Viesques, 33204, Gijon, Spain,<br />
adenso@epsig.uniovi.es<br />
Chair: Ben Lev, Decision Sciences, Drexel University, LeBow<br />
College of Business, 101 N. 33rd st., 19104, Philadelphia, Pa, United<br />
States, blev@drexel.edu
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