Explanipedia

Feedback-integrated prompt optimiser for problem formulation Open

Pivithuru Thejan Amarasinghe, Su Nguyen, Yuan Sun, Damminda Alahakoon · 2025

Problem formulation is a critical yet expertise-intensive step in optimisation modelling. Automating this process offers a promising solution, but requires effective methods to replicate the reasoning and decision-making processes that are…

Platelet-rich plasma therapy for meibomian gland dysfunction and dry eye: A mini review Open

Su Nguyen, Phuc Van Pham · 2024

A Hierarchical Machine Learning Method for Detection and Visualization of Network Intrusions from Big Data Open

Jinrong Wu, Su Nguyen, Thimal Kempitiya, Damminda Alahakoon · 2024

Machine learning is regarded as an effective approach in network intrusion detection, and has gained significant attention in recent studies. However, few intrusion detection methods have been successfully applied to detect anomalies in la…

Evolutionary Multi-Objective Optimisation for Fairness-Aware Self Adjusting Memory Classifiers in Data Streams Open

Pivithuru Thejan Amarasinghe, Diem Pham, Binh Tran, Su Nguyen, Yuan Sun , et al. · 2024

This paper introduces a novel approach, evolutionary multi-objective optimisation for fairness-aware self-adjusting memory classifiers, designed to enhance fairness in machine learning algorithms applied to data stream classification. With…

Transforming Customer Digital Footprints into Decision Enablers in Hospitality Open

Achini Adikari, Su Nguyen, Rashmika Nawaratne, Daswin De Silva, Damminda Alahakoon · 2024

The proliferation of online hotel review platforms has prompted decision-makers in the hospitality sector to acknowledge the significance of extracting valuable information from this vast source. While contemporary research has primarily f…

Fairness optimisation with multi-objective swarms for explainable classifiers on data streams Open

Diem Pham, Binh Tran, Su Nguyen, Damminda Alahakoon, Mengjie Zhang · 2024

Recently, advanced AI systems equipped with sophisticated learning algorithms have emerged, enabling the processing of extensive streaming data for online decision-making in diverse domains. However, the widespread deployment of these syst…

Enhancing constraint programming via supervised learning for job shop scheduling Open

Yuan Sun, Su Nguyen, Dhananjay Thiruvady, Xiaodong Li, Andreas Ernst , et al. · 2024

A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types Open

Jinrong Wu, Su Nguyen, Damminda Alahakoon, Daswin De Silva, Nishan Mills , et al. · 2024

Building energy baseline models, particularly machine learning-based models, are a core aspect in the evaluation of building energy performance to identify inefficient energy consumption behavior. In smart city design, energy planners and …

Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty Open

Dhananjay Thiruvady, Su Nguyen, Yuan Sun, Fatemeh Shiri, Nayyar A. Zaidi , et al. · 2024

Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty

Genetic-based Constraint Programming for Resource Constrained Job Scheduling Open

Su Nguyen, Dhananjay Thiruvady, Yuan Sun, Mengjie Zhang · 2024

Resource constrained job scheduling is a hard combinatorial optimisation problem that originates in the mining industry. Off-the-shelf solvers cannot solve this problem satisfactorily in reasonable timeframes, while other solution methods …

An efficient merge search matheuristic for maximising net present value in project scheduling Open

Dhananjay Thiruvady, Su Nguyen, Christian Blum, Andreas Ernst · 2024

Resource constrained project scheduling (RCPS) is an important combinatorial optimisation problem with many practical applications. With complex requirements such as precedence constraints, limited resources, and finance-based objectives, …

Container Dwell-Time Predictive Modelling: An Application of Ml Algorithms Open

Prem Chhetri, Su Nguyen, Victor Gekara, Sharad Sharma · 2024

Language Models for Business Optimisation with a Real World Case Study in Production Scheduling Open

Pivithuru Thejan Amarasinghe, Su Nguyen, Yuan Sun, Damminda Alahakoon · 2023

Business optimisation has been used extensively to determine optimal solutions for challenging business operations. Problem formulation is an important part of business optimisation as it influences both the validity of solutions and the e…

Leveraging explainable AI for enhanced decision making in humanitarian logistics: An Adversarial CoevoluTION (ACTION) framework Open

Su Nguyen, Greg O’Keefe, Sobhan Arisian, Kerry Trentelman, Damminda Alahakoon · 2023

This study examines the potential of AI-enabled wargames to enhance strategic decisionmaking in humanitarian assistance and disaster relief (HADR). We introduce an Adversarial CoevoluTION (ACTION) framework, which showcases AI’s capacity t…

Forecasting container freight rates using the Prophet forecasting method Open

Naima Saeed, Su Nguyen, Kevin Cullinane, Victor Gekara, Prem Chhetri · 2023

This study applies three innovative methods in forecasting container freight rates. Firstly, we extracted 471 major disruptive events from the 'Lloyds List' database from 2010 until 2020, that may affect freight rates. Secondly, we use Mac…

A Robust Artificial Intelligence Approach with Explainability for Measurement and Verification of Energy Efficient Infrastructure for Net Zero Carbon Emissions Open

Harsha Moraliyage, Sanoshi Dahanayake, Daswin De Silva, Nishan Mills, Prabod Rathnayaka , et al. · 2022

Rapid urbanization across the world has led to an exponential increase in demand for utilities, electricity, gas and water. The building infrastructure sector is one of the largest global consumers of electricity and thereby one of the lar…

Enhancing Constraint Programming via Supervised Learning for Job Shop Scheduling Open

Yuan Sun, Su Nguyen, Dhananjay Thiruvady, Xiaodong Li, Andreas Ernst , et al. · 2022

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 variable to explore first in the solving process has a si…

Adaptive Population-based Simulated Annealing for Uncertain Resource Constrained Job Scheduling Open

Dhananjay Thiruvady, Su Nguyen, Yuan Sun, Fatemeh Shiri, Nayyar A. Zaidi , et al. · 2022

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 of resources. Large mining companies are interested in optimally allocating the…

An Efficient Merge Search Matheuristic for Maximising the Net Present Value of Project Schedules Open

Dhananjay Thiruvady, Su Nguyen, Christian Blum, Andreas Ernst · 2022

Resource constrained project scheduling is an important combinatorial optimisation problem with many practical applications. With complex requirements such as precedence constraints, limited resources, and finance-based objectives, finding…

XMAP: eXplainable mapping analytical process Open

Su Nguyen, Binh Tran · 2021

An investigation of ensemble combination schemes for genetic programming based hyper-heuristic approaches to dynamic job shop scheduling Open

Cheol Park, Yi Mei, Su Nguyen, Gang Chen, Mengjie Zhang · 2021

Genetic programming based hyper-heuristic (GP-HH) approaches that evolve ensembles of dispatching rules have been effectively applied to dynamic job shop scheduling (JSS) problems. Ensemble GP-HH approaches have been shown to be more robus…

An investigation of ensemble combination schemes for genetic programming based hyper-heuristic approaches to dynamic job shop scheduling Open

Cheol Park, Yi Mei, Su Nguyen, Gang Chen, Mengjie Zhang · 2021

Genetic programming based hyper-heuristic (GP-HH) approaches that evolve ensembles of dispatching rules have been effectively applied to dynamic job shop scheduling (JSS) problems. Ensemble GP-HH approaches have been shown to be more robus…

Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling Open

Fangfang Zhang, Yi Mei, Su Nguyen, Kay Chen Tan, Mengjie Zhang · 2021

Evolutionary multitask learning has achieved great success due to its ability to handle multiple tasks simultaneously. However, it is rarely used in the hyperheuristic domain, which aims at generating a heuristic for a class of problems ra…

An efficient feature selection algorithm for evolving job shop scheduling rules with genetic programming Open

Yi Mei, Su Nguyen, Bing Xue, Mengjie Zhang · 2021

Automated design of job shop scheduling rules using genetic programming as a hyper-heuristic is an emerging topic that has become more and more popular in recent years. For evolving dispatching rules, feature selection is an important issu…

An efficient feature selection algorithm for evolving job shop scheduling rules with genetic programming Open

Yi Mei, Su Nguyen, Bing Xue, Mengjie Zhang · 2021

Automated design of job shop scheduling rules using genetic programming as a hyper-heuristic is an emerging topic that has become more and more popular in recent years. For evolving dispatching rules, feature selection is an important issu…

Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling Open

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang, Kay Chen Tan · 2021

Dynamic flexible job shop scheduling (JSS) is an important combinatorial optimization problem with complex routing and sequencing decisions under dynamic environments. Genetic programming (GP), as a hyperheuristic approach, has been succes…

Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling Open

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang · 2021

Dynamic flexible job shop scheduling (JSS) has received widespread attention from academia and industry due to its practical application value. It requires complex routing and sequencing decisions under unpredicted dynamic events. Genetic …

Correlation Coefficient-Based Recombinative Guidance for Genetic Programming Hyperheuristics in Dynamic Flexible Job Shop Scheduling Open

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang · 2021

Dynamic flexible job shop scheduling (JSS) is a challenging combinatorial optimization problem due to its complex environment. In this problem, machine assignment and operation sequencing decisions need to be made simultaneously under the …

People-Centric Evolutionary System for Dynamic Production Scheduling Open

Su Nguyen, Mengjie Zhang, Damminda Alahakoon, Kay Chen Tan · 2020

Evolving production scheduling heuristics is a challenging task because of the dynamic and complex production environments and the interdependency of multiple scheduling decisions. Different genetic programming (GP) methods have been devel…

A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules Open

Su Nguyen, Yi Mei, Bing Xue, Mengjie Zhang · 2020

© 2018 Massachusetts Institute of Technology. Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine le…

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