A5046309576- Scheduling and Optimization Algorithms
- Scheduling and Timetabling Solutions
- Resource-Constrained Project Scheduling
- Assembly Line Balancing Optimization
- Vehicle Routing Optimization Methods
- Constraint Satisfaction and Optimization
- Metaheuristic Optimization Algorithms Research
- Blockchain Technology Applications and Security
- Manufacturing Process and Optimization
- Topic Modeling
- Environmental Impact and Sustainability
- Advanced Manufacturing and Logistics Optimization
- Optimization and Packing Problems
- Complex Network Analysis Techniques
- Advanced Graph Theory Research
- Advanced Text Analysis Techniques
- BIM and Construction Integration
- Stock Market Forecasting Methods
- Mining Techniques and Economics
- Land Use and Ecosystem Services
- Amphibian and Reptile Biology
- Sentiment Analysis and Opinion Mining
- Complex Systems and Time Series Analysis
- Hospital Admissions and Outcomes
- Neurological disorders and treatments
Deakin University
2019-2024
Monash University
2007-2019
Commonwealth Scientific and Industrial Research Organisation
2009-2016
Market Intelligence Strategy Centre (Australia)
2015
Australian Regenerative Medicine Institute
2004-2014
Huntington's disease is a progressive neurodegenerative disorder that results in deterioration and atrophy of various brain regions.To assess the functional connectivity between prefrontal regions patients with disease, compared normal controls, using magnetic resonance imaging.20 17 matched controls performed Simon task known to activate lateral anterior cingulate cortical regions. The was hypothesised be impaired interest, selected from both hemispheres, dorsal cortex.Controls showed...
Data breaches and security incidents are becoming increasingly costly statistics show that hackers highly motivated to acquire confidential data as the financial benefits substantial. Hence, business has become a top priority be compromised. Threat Intelligence been recently introduced by organisations means gain greater visibility of cyber threats, especially breaches, in order better protect their digital assets. A well-planned implementation threat intelligence enables predict (at least...
The total capital in cryptocurrency markets is around two trillion dollars 2022, which almost the same as Apple’s market capitalisation at time. Increasingly, cryptocurrencies have become established financial with an enormous number of transactions and trades happening every day. Similar to other systems, price prediction one main challenges trading. Therefore, application artificial intelligence, tools prediction, has emerged a recently popular subject investigation domain. Since machine...
Constraint programming (CP) is a powerful technique for solving constraint satisfaction and optimization problems. In CP solvers, the variable ordering strategy used to select which explore first in process has significant impact on solver effectiveness. To address this issue, we propose novel based supervised learning, evaluate context of job shop scheduling Our learning-based methods predict optimal solution problem instance use predicted order variables solvers. Unlike traditional...
Transporting ore from mines to ports is of significant interest in mining supply chains. These operations are commonly associated with growing costs and a lack resources. Large companies interested optimally allocating resources reduce operational costs. This problem has been previously investigated as resource constrained job scheduling (RCJS). While number optimisation methods have proposed tackle the deterministic problem, uncertainty availability, an inevitable challenge operations,...
High penetration of renewable energy generation in the electricity grid presents power system operators with challenges, including voltage instability, mainly due to fluctuating generation. To address challenges that arise from intermittent generation, we explore introduction community batteries provide an elegant solution for storing excess resources (RESs) and reverting peak demand periods. In particular, determining optimal battery type size along minimum costs is challenging. Moreover,...
Matheuristics have been gaining in popularity for solving combinatorial optimisation problems recent years. This new class of hybrid method combines elements both mathematical programming intensification and metaheuristic searches diversification. A approach this direction has to build a neighbourhood integer programs by merging information from several heuristic solutions, namely construct, solve, merge adapt (CMSA). In study, we investigate alongside closely related novel approach—merge...
Resource constraint job scheduling is an important combinatorial optimization problem with many practical applications. This aims at determining a schedule for executing jobs on machines satisfying several constraints (e.g., precedence and resource constraints) given shared central while minimizing the tardiness of jobs. Due to complexity problem, exact, heuristic, hybrid methods have been attempted. Despite their success, scalability still major issue existing methods. In this study, we...
Abstract We developed a machine learning based surrogate model to identify sustainability pathways through rapid scenario generation and defined the safe operating space for achieving them via discovery. trained replicate Land‐Use Trade‐Offs integrated of Australian land system. Latin hypercube sampling was used create many scenarios exploring impact uncertainties in key drivers including future socio‐economic development, climate change mitigation, agricultural productivity at granular...
In this study, we investigate a hybrid Lagrangian relaxation ant colony optimisation for version of the car sequencing problem. Several cars are required to be scheduled on an assembly line and each requires number options such as sunroof and/or air conditioning. These sequenced that sub-sequences specific sizes may only include limited any option. While is usually hard constraint, in study treat it soft constraint further require utilisation modulated across sequence leading We various...
The growth of market capitalisation and the number altcoins (cryptocurrencies other than Bitcoin) provide investment opportunities complicate prediction their price movements. A significant challenge in this volatile relatively immature is problem predicting cryptocurrency prices which needs to identify factors influencing these prices. focus study investigate altcoin prices, have been investigated from a causal analysis perspective using Bayesian networks. In particular, studying nature...
Habitat loss is a key factor in the ongoing freshwater biodiversity crisis. A promising way to help tackle rapid decline improve potential for artificial wetlands provide habitat aquatic wildlife. Farm dams (also known as agricultural ponds) are among most abundant waterbodies landscapes and can act "oases" against droughts many species. Despite their prominent role agriculture, predictive models evaluate ecological yet emerge. Here we use continental-scale data set of 104,013 audio...