Australian Society for Operations Research
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2015 Program

Note: there is now no "default" venue for the monthly lectures!

Melbourne time

Scheduled Events for 2015

September 30Lecture Andreas Ernst A retrospective of over two decades of Operations Research at CSIRO
September 23Lecture Asef Nazari Expansions on Land-use Trade-off Optimisation (LUTO)
September 2Lecture Kristian Rotaru Risk information processing and decision-making with strategic performance measurement systems: an eye-tracking study
August 19Lecture Carleton Coffrin A Brief History of Optimal Power Flow
August 5Lecture Aldeida Aleti Measuring instance difficulty for combinatorial optimisation problems
June 17Lecture Hadi Charkhgard A Polynomial Time Algorithm to Solve a Class of Optimization Problems with a Multi-linear Objective Function and Affine Constraints
May 20LectureAxel Bender Degeneracy - Design Principle for Adaptable and Robust Complex Systems
March 18AGM
March 18LectureStefano Penazzi Issues, challenges, models and tools for the design, management and control of job-shop manufacturing system in food industry

Venue:Room 7.84, Building H, Monash Caulfield

Time: 3:30PM, Wed, September 30, 2015

Program: Lecture by Andreas Ernst, CSIRO

Topic:: A retrospective of over two decades of Operations Research at CSIRO

The Operations Research group at CSIRO was formed in the early 1990s and since then has been a significant part of the OR scene in Australia. With the departure of a number of key members of the group and the imminent merger between NICTA and the CSIRO, the OR group will cease to exist in its current form. This talk will look back over the past 20 years at some of the highlights of what has been achieved by the group. This includes discussion of how a small project for Australia Post inspired a stream of research into hub location problems; the development of rostering optimisation methods and the challenges of commercialising it; and the range of interesting OR problems in bulk material (mining) supply chains. The talk will also be used to comment on the developments in OR in Australia more widely and the likely trends into the future.

Venue:RMIT AGR (City Campus, building 8 floor 9 room 66)

Time: 5:30PM, Wed, September 23, 2015

Program: Lecture by Asef Nazari, CSIRO

Topic:: Expansions on Land-use Trade-off Optimisation (LUTO)

CSIRO has previously developed a model of land-use trade-offs that considers the possible evolution of agricultural land areas in Australia over the next 40 years. This can be modelled as a large scale multi-stage linear programming problem. However, acquiring the expected outcome requires solving the large scale LP problem which takes more than one hour to solve for a single year. In this regard, we developed a combination of aggregation-disaggregation technique with the concept of column generation to solve the large scale LP problem originating from land use management in the Australian agricultural sector in a shorter amount of CPU time. In addition, increasing demand for greener energy alternatives are putting more pressure on the use of agricultural land for not just food productions but also biofuels, carbon sequestration, biodiversity and other non-traditional uses. A key question is how this is going to impact not only the land use but also the agricultural supply chains that process the outputs of the land use. In this talk we also initiate the question of locations of processing centres and land use in an integrated optimisation model. Here we consider in addition the construction of some processing centres for bio-fuel, bio-energy, livestock facilities and so forth, which introduces a new combinatorial aspect to the model. The decisions of land use and the location of processing centres are interlinked as transport costs based on distances are often instrumental in determining the economic viability of some of the land uses and conversely economies of scale are necessary to justify investment in processing plants. We introduce a model containing both problems of a land allocation and a facility location simultaneously which results in a large scale mixed integer linear programming (MILP) problem and therefore is computationally difficult to solve, and we will cover some of the computational difficulties.

About the Speaker: Asef was awarded his PhD in 2009 on the topic of developing derivative free algorithms for non-smooth optimisation problems from the University of Ballarat. Immediately after his PhD, he was appointed as a research associate at the UniSA to conduct research on the optimal expansion of a power system. Since 2013 he has been employed by CSIRO to be involved in several industrial projects

Venue:Building H. Room 7.84, Monash University Caulfield Campus

Time: 3:30PM, Wed, September 2, 2015

Program: Lecture by Kristian Rotaru, Monash University

Topic:: Risk information processing and decision-making with strategic performance measurement systems: an eye-tracking study

To address the limitations of the traditional strategic performance measurement systems (SPMSs) in visualizing risk and preventing excessive managerial risk-taking, a number of research studies proposed to extend the functionality of SPMSs by incorporating risk information into traditional SPMSs, such as balanced scorecards. Thus, despite the growing calls of practitioners and researchers on combining performance and risk measures as part of an extended framework, there is a lack of uniform vision about what constitutes such a framework. The aim of this study is to investigate how the representation of risk-related information (characteristics of risk events and key risk indicators) in SPMSs influences the identification and processing of this information in managerial risky decision making. This study benefits from the use of eye-tracking methodology in a laboratory experiment, which allowed to acquire better understanding of the cognitive processes and the subsequent behavioural response associated with managerial risky decision-making when using SPMSs as a tool for decision support.

About the Speaker: Dr Kristian Rotaru (PhD in Economics, PhD in Information Systems/Risk Management) works in the domains of risk modelling and decision making. He is a Member of the Editorial Review Board of the Journal of Operations Management. At Monash Business School, Kristian leads the Risk Analysis, Judgement and Decision-Making cross-disciplinary research team that focuses on integration of normative research informed by analytical and simulation modelling methods and descriptive research, informed by laboratory and field experiments. In his research he adopts a variety of research methods, including market data analysis, conceptual, analytical and simulation modelling and laboratory experiments (involving the use of eye-tracking and electroencephalography technology). Kristian lectures Business Analytics, Accounting Information Systems and Financial Modelling units.

Venue:Building H. Room 7.84, Monash University Caulfield Campus

Time: 3:30PM, Wed, August 19, 2015

Program: Lecture by Carleton Coffrin, NICTA

Topic:: A Brief History of Optimal Power Flow

The non-convex nonlinear AC power flow equations form the core of a wide range of power network decision support applications. One of the most notable being the Optimal Power Flow (OPF) problem, which was first described over 50 years ago and now plays an essential role in the minute-by-minute operations of modern power systems. This talk will begin with a review of the foundations of the OPF problem and then show how a sequence of recent discoveries from 2006, 2008, 2012, and 2014 have transformed our understanding of this fundamental power network optimization task.

About the Speaker: Carleton Coffrin currently works as a staff researcher in NICTA-ORG's Future Energy Systems initiative where he investigates how optimization technology can aid in building a sustainable energy future. Before joining this group at NICTA, Carleton conducted his Ph.D. studies at Brown University and Los Alamos National Laboratory in the area of hybrid optimization for disaster management, under the supervision of Pascal Van Hentenryck.

Venue:Building H. Room 7.84, Monash University Caulfield Campus

Time: 3:30PM, Wed, August 5, 2015

Program: Lecture by Aldeida Aleti, Monash University

Topic:: Measuring instance difficulty for combinatorial optimisation problems

No algorithm can outperform all other algorithms in all problem instances. The success of any optimisation method depends on critical features of the problem instances at hand. I will discuss how to adequately characterise the features of a problem instance that have impact on difficulty in terms of algorithmic performance, and how such features can be defined and measured for various optimisation problems.

About the Speaker: Aldeida is a lecturer and DECRA research fellow at the Faculty of IT, Monash University. Her research interests include optimisation of combinatorial problems, analysis of fitness landscapes, adaptive optimisation, robust optimisation, software quality and design, and software testing.

Venue: RMIT, Building 80 Floor 5 Room 12, Swanston St, City

Time: 4:30PM, Wed, June 17, 2015

Program: Lecture by Hadi Charkhgard, University of Newcastle

Topic:: A Polynomial Time Algorithm to Solve a Class of Optimization Problems with a Multi-linear Objective Function and Affine Constraints

In this talk, I will present the first polynomial-time linear programming based algorithm for a class of optimization problems with a multi-linear objective function and affine constraints. This class of optimization problems arises naturally in a number of settings in game theory, such as the bargaining problem, linear Fisher markets, and Kelly capacity allocation markets, but has applications in other fields of study as well. The algorithm computes an optimal solution by solving at most O(p^3) linear programs, where p is the number of variables in the multi-linear objective function.

About the Speaker: Hadi Charkhgard received his Master's degree in Industrial Engineering from Sharif University of Technology in Iran. Following that, in 2012, he started his Ph.D. research (in the field of Operations Research) under the supervision of Prof. Martin Savelsbergh, Prof. Natashia Boland, and Dr. Masoud Talebian at the University of Newcastle. His research interests lie mainly in the fields of multi-objective optimization and algorithmic game theory. Hadi is expected to complete his Ph.D. by August 2015. He has written 10 papers during his Ph.D. research, and his papers are accepted or under review in highly ranked journals in OR such as INFORMS Journal on Computing, Mathematical Programming Computation, and Journal of Global optimization.

Venue: RMIT 080.05.012 (Building 80, level 5 room 12)

Time: 5:30PM, Wed, May, 2015

Program: Lecture by Axel Bender (DSTO)

Topic:: Degeneracy - Design Principle for Adaptable and Robust Complex Systems

Understanding how systems can be designed to be both robust and adaptable is fundamental to research in optimisation, evolution, and complex systems science. A recent theory on the origins of systemic flexibility in biological systems has proposed that degeneracy - the realisation of multiple, functionally versatile components with contextually overlapping functional redundancy - is a primary determinant of the robustness and adaptability found in living systems. While degeneracy's contribution to biological flexibility is well documented, it is somehow underrepresented in operations research and systems engineering.

This talk presents the principles of degeneracy-based design and illustrates its effect on robustness and adaptability in the context of a strategic resource planning problem. A simple model will be presented that captures the most important dynamics of a vehicle fleet resource planning problem, namely: changes in the assignment of vehicles to tasks, changes in the composition of vehicles that make up a fleet, changes in the tasks that must be executed during fleet operations, and changes in the composition of tasks at a timescale comparable to the timescale for changes in fleet composition. Simulating this model in an evolutionary computation environment demonstrates that degeneracy improves the robustness and adaptability of a vehicle fleet towards unpredicted changes in task requirements without incurring costs to fleet efficiency.

The generic characteristics of the presented model allows for the generalisation of some of the findings. The talk thus will mention and discuss operations research and engineering examples where degeneracy-based design may improve the adaptability and robustness of complex systems, including military force structures, digitally resilient technology, and organisational innovation.

About the Speaker: Axel Bender received his PhD in theoretical particle physics from the University of Tubingen, Germany, in 1994. Subsequently, he held postdoctoral research positions at the Argonne National Laboratory, USA, and the University of Adelaide, Australia, and a Research Officer position at the National Centre for Vocational Education Research, Adelaide. In 2003, he joined the Defence Science and Technology Organisation (DSTO) as an Operations Researcher.

In his early days at DSTO, Axel supported military experimentation and cost-capability trade-off analyses of defence systems. Following this, he led interdisciplinary science teams in support of defence capability development - the problem domains spanning land combat, manoeuvre support, land mobility, airlift, combat service support, and amphibious capabilities. He is currently heading Land Division's Advanced Vehicle Systems Science group which aims to develop and demonstrate concepts, enablers and technologies for adaptable and resilient sensor-effector services in and between land combat vehicles.

Since joining DSTO, Axel has co-authored around 50 journal articles, scholarly book chapters and conference papers in a variety of fields including computational intelligence, biologically inspired systems, artificial life, theoretical biology, risk management, strategic planning, multi-objective optimisation, fleet management, scheduling and routing, bin packing, and game theory. Axel's current research interests are in the justifiability of decision support analysis; complex systems design for robustness and adaptability through networked buffers; and the application of evolutionary computation in risk management.

Venue: RMIT Access Grid Room, 8.8.13 (Building 8, level 8, room 13)

Time: 5PM, Wed March 18, 2015

Program: AGM

Venue: RMIT Access Grid Room, 8.8.13 (Building 8, level 8, room 13)

Time: 5:30PM, Wed March 18, 2015

Program: Lecture by Stefano Penazzi, Department of Industrial Engineering, Bologna University (Italy)

Topic:: Issues, challenges, models and tools for the design, management and control of job-shop manufacturing system in food industry*

The food processing industry is growing with retailing and catering supply chains. Efficiency, safety, quality, service level and, sustainability are key objectives in both food production and distribution systems. In particular, with the raising complexity of food product to match consumers requirements and food habits, the food production system are progressively shifting from processing line to processing job-shops as complex manufacturing systems in presence of multiple items (i.e., food, toppings, dressings, ingredients), resources and machines, and complex working cycles. Generic working cycle is realized across multiple tasks (i.e., operations), carried out by different human or automatic resources in multiple working stations. These systems present several storage and buffering areas and many assembly tasks, which are critical for perishable products sensible to environmental and physical stresses. Logistic efficiency, cost reduction, food quality, food safety are then key goals in managing the food production system.

The design and control of food job-shop production system involves long and mid-terms strategic decisions (1), e.g., the plant layout, the number of machines or working stations, mid and short terms tactical decisions (2), e.g., the planning of ingredients purchasing, the production planning, and operational decisions (3), e.g., the tasks scheduling constrained by capacities, priority, working cycle precedence, safety limitations. The aim of the planners is to fulfill the food demand and the service level minimizing the production and logistic costs,, the environmental impacts,, by controlling the residual shelf life and the product quality and safety.

This study presents an original conceptual framework for the integrated design, management and control of a job-shop production system in food industry. The framework is based on the development and application of different modelling and solving approaches and techniques. In particular, a simulation based supporting decision model is proposed. A case study from an Italian food catering company is also illustrated.

* Joint work with Simon Dunstall, Emilio Ferrari, Riccardo Manzini
The previous big event

IFORS 2011 Conference
July 10-15, 2011, Melbourne, Australia