Webinar
Stress-testing Algorithms, Solvers, and Models via Instance Space Analysis
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms.
June 3, 2025
10:00 AM - 11:30 AM PST
Webinar
Stress-testing Algorithms, Solvers, and Models via Instance Space Analysis
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms.
June 3, 2025
10:00 AM - 11:30 AM PST
Webinar
Stress-testing Algorithms, Solvers, and Models via Instance Space Analysis
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms.
June 3, 2025
10:00 AM - 11:30 AM PST
Event Recap
Our society is critically dependent on reliable algorithms, especially optimisation algorithms to support complex decision making, but establishing trust is a growing concern. How do we know that our algorithmic choices – whether it be a heuristic or exact solver, or a model, or parameter configurations – are reliable in practice? This vexing issue relies on testing algorithms with enough unbiased test instances to gain insights into strengths and weaknesses under various conditions.
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms. ISA exposes the strengths and weaknesses of algorithms and supports the generation of rich and diverse test problems to understand algorithm reliability under a variety of conditions.
The methodology has been made available via an online tool (matilda.unimelb.edu.au) that has been adopted worldwide by researchers in many fields, and is supporting industry partners keen to avoid disasters when deploying critical algorithms. The webinar will use several case studies from timetabling and bin packing to highlight how insights into performance of heuristics, MIP models or solvers can be obtained by generating and testing diverse instances with ISA.
Event Recap
Our society is critically dependent on reliable algorithms, especially optimisation algorithms to support complex decision making, but establishing trust is a growing concern. How do we know that our algorithmic choices – whether it be a heuristic or exact solver, or a model, or parameter configurations – are reliable in practice? This vexing issue relies on testing algorithms with enough unbiased test instances to gain insights into strengths and weaknesses under various conditions.
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms. ISA exposes the strengths and weaknesses of algorithms and supports the generation of rich and diverse test problems to understand algorithm reliability under a variety of conditions.
The methodology has been made available via an online tool (matilda.unimelb.edu.au) that has been adopted worldwide by researchers in many fields, and is supporting industry partners keen to avoid disasters when deploying critical algorithms. The webinar will use several case studies from timetabling and bin packing to highlight how insights into performance of heuristics, MIP models or solvers can be obtained by generating and testing diverse instances with ISA.
Event Recap
Our society is critically dependent on reliable algorithms, especially optimisation algorithms to support complex decision making, but establishing trust is a growing concern. How do we know that our algorithmic choices – whether it be a heuristic or exact solver, or a model, or parameter configurations – are reliable in practice? This vexing issue relies on testing algorithms with enough unbiased test instances to gain insights into strengths and weaknesses under various conditions.
This talk will provide a brief introduction to Instance Space Analysis as a methodology that provides a mathematically rigorous foundation for “stress-testing” algorithms. ISA exposes the strengths and weaknesses of algorithms and supports the generation of rich and diverse test problems to understand algorithm reliability under a variety of conditions.
The methodology has been made available via an online tool (matilda.unimelb.edu.au) that has been adopted worldwide by researchers in many fields, and is supporting industry partners keen to avoid disasters when deploying critical algorithms. The webinar will use several case studies from timetabling and bin packing to highlight how insights into performance of heuristics, MIP models or solvers can be obtained by generating and testing diverse instances with ISA.
Speaker
Meet Your Expert Speaker
Learn from the best in the industry.
Kate Smith-Miles
Pro Vice-Chancellor (Research Capability)
Professor Kate Smith-Miles is a leading Australian mathematician and the Pro Vice-Chancellor (Research Capability) at The University of Melbourne, where she also holds a Melbourne Laureate Professorship in Applied Mathematics. She directs the ARC Training Centre OPTIMA, which focuses on optimisation technologies.
With a PhD in Electrical Engineering and a B.Sc(Hons) in Mathematics from The University of Melbourne, her academic career began in 1996. She has authored two books and around 300 publications in neural networks, optimisation, and data mining, and has supervised over 30 PhD students. Her leadership roles have included positions at Monash University, President of the Australian Mathematical Society, and ARC College of Experts member.
She has secured over AUD$20 million in grants, including a prestigious Georgina Sweet Laureate Fellowship. Her Instance Space Analysis work led to the development of MATILDA, a benchmarking tool for algorithms. Professor Smith-Miles has received numerous accolades, including the AO in the 2024 King’s Birthday Honours and fellowships in major scientific societies.
A dedicated mentor and advocate for women in STEM, she also consults widely with industry, applying her expertise in optimisation and intelligent systems to real-world challenges. Her career reflects excellence in research, leadership, and service to the mathematical sciences.
Speaker
Meet Your Expert Speaker
Learn from the best in the industry.
Kate Smith-Miles
Pro Vice-Chancellor (Research Capability)
Professor Kate Smith-Miles is a leading Australian mathematician and the Pro Vice-Chancellor (Research Capability) at The University of Melbourne, where she also holds a Melbourne Laureate Professorship in Applied Mathematics. She directs the ARC Training Centre OPTIMA, which focuses on optimisation technologies.
With a PhD in Electrical Engineering and a B.Sc(Hons) in Mathematics from The University of Melbourne, her academic career began in 1996. She has authored two books and around 300 publications in neural networks, optimisation, and data mining, and has supervised over 30 PhD students. Her leadership roles have included positions at Monash University, President of the Australian Mathematical Society, and ARC College of Experts member.
She has secured over AUD$20 million in grants, including a prestigious Georgina Sweet Laureate Fellowship. Her Instance Space Analysis work led to the development of MATILDA, a benchmarking tool for algorithms. Professor Smith-Miles has received numerous accolades, including the AO in the 2024 King’s Birthday Honours and fellowships in major scientific societies.
A dedicated mentor and advocate for women in STEM, she also consults widely with industry, applying her expertise in optimisation and intelligent systems to real-world challenges. Her career reflects excellence in research, leadership, and service to the mathematical sciences.
Speaker
Meet Your Expert Speaker
Learn from the best in the industry.
Pro Vice-Chancellor (Research Capability)
Kate Smith-Miles
Professor Kate Smith-Miles is a leading Australian mathematician and the Pro Vice-Chancellor (Research Capability) at The University of Melbourne, where she also holds a Melbourne Laureate Professorship in Applied Mathematics. She directs the ARC Training Centre OPTIMA, which focuses on optimisation technologies.
With a PhD in Electrical Engineering and a B.Sc(Hons) in Mathematics from The University of Melbourne, her academic career began in 1996. She has authored two books and around 300 publications in neural networks, optimisation, and data mining, and has supervised over 30 PhD students. Her leadership roles have included positions at Monash University, President of the Australian Mathematical Society, and ARC College of Experts member.
She has secured over AUD$20 million in grants, including a prestigious Georgina Sweet Laureate Fellowship. Her Instance Space Analysis work led to the development of MATILDA, a benchmarking tool for algorithms. Professor Smith-Miles has received numerous accolades, including the AO in the 2024 King’s Birthday Honours and fellowships in major scientific societies.
A dedicated mentor and advocate for women in STEM, she also consults widely with industry, applying her expertise in optimisation and intelligent systems to real-world challenges. Her career reflects excellence in research, leadership, and service to the mathematical sciences.
