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Multiple landscape measure-based approach for dynamic optimization problems Open
Many practical decision-making problems involve dynamic scenarios, where the decision variables, conditions and/or parameters of their optimization models change over time. Such problems are known as dynamic optimization problems (DOPs). A…
View article: Large-scale evolutionary optimization: A review and comparative study
Large-scale evolutionary optimization: A review and comparative study Open
Large-scale global optimization (LSGO) problems have widely appeared in various real-world applications. However, their inherent complexity, coupled with the curse of dimensionality, makes them challenging to solve. Continuous efforts have…
Towards Mitigating ChatGPT's Negative Impact on Education: Optimizing Question Design through Bloom's Taxonomy Open
The popularity of generative text AI tools in answering questions has led to concerns regarding their potential negative impact on students' academic performance and the challenges that educators face in evaluating student learning. To add…
Planning-Assisted Context-Sensitive Autonomous Shepherding of Dispersed Robotic Swarms in Obstacle-Cluttered Environments Open
Robotic shepherding is a bio-inspired approach to autonomously guiding a swarm of agents towards a desired location. The research area has earned increasing research interest recently due to the efficacy of controlling a large number of ag…
View article: Evolutionary Constrained Optimization with Dynamic Changes and Uncertainty in the Objective Function
Evolutionary Constrained Optimization with Dynamic Changes and Uncertainty in the Objective Function Open
Many real-life optimization problems involve dynamic changes with uncertain parameters and data, which make the decision-making process challenging. Although there are some studies on solving dynamic or uncertain problems, there is limited…
View article: Modified Differential Evolution Algorithm for Solving Dynamic Optimization with Existence of Infeasible Environments
Modified Differential Evolution Algorithm for Solving Dynamic Optimization with Existence of Infeasible Environments Open
Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instanc…
View article: Revisiting Implicit and Explicit Averaging for Noisy Optimization
Revisiting Implicit and Explicit Averaging for Noisy Optimization Open
Explicit and implicit averaging are two well-known strategies for noisy optimization. Both strategies can counteract the disruptive effect of noise; however, a critical question remains: which one is more efficient? This question has been …
View article: Upgrade of the CMS resistive plate chambers for the high luminosity LHC
Upgrade of the CMS resistive plate chambers for the high luminosity LHC Open
During the upcoming High Luminosity phase of the Large Hadron Collider (HL-LHC), the integrated luminosity of the accelerator will increase to 3000 fb −1 . The expected experimental conditions in that period in terms of background rates, e…
View article: Static and Dynamic Multimodal Optimization by Improved Covariance Matrix Self-Adaptation Evolution Strategy With Repelling Subpopulations
Static and Dynamic Multimodal Optimization by Improved Covariance Matrix Self-Adaptation Evolution Strategy With Repelling Subpopulations Open
The covariance matrix self-adaptation evolution strategy with repelling subpopulations (RS-CMSA-ES) is one of the most successful multimodal optimization (MMO) methods currently available. However, some of its components may become ineffic…
View article: Pro-Reactive Approach for Project Scheduling Under Unpredictable Disruptions
Pro-Reactive Approach for Project Scheduling Under Unpredictable Disruptions Open
Existing solution approaches for handling disruptions in project scheduling use either proactive or reactive methods. However, both techniques suffer from some drawbacks that affect the performance of the optimization process in obtaining …
View article: Project portfolio selection with defense capability options
Project portfolio selection with defense capability options Open
This paper proposes a novel formulation of the project portfolio selection and scheduling problem inspired by the Future Defense Force Design process in the context of the Australian Defence Force capability development. The core objective…
View article: Modular Analysis and Development of a Genetic Algorithm with Standardized Representation for Resource-Constrained Project Scheduling
Modular Analysis and Development of a Genetic Algorithm with Standardized Representation for Resource-Constrained Project Scheduling Open
There has been a considerable amount of research on the development of metaheuristic methods for resource-constrained project scheduling problems. Early methods followed the building blocks and even the formulation of well-understood metah…
View article: CMS RPC background — studies and measurements
CMS RPC background — studies and measurements Open
The expected radiation background in the CMS RPC system has been studied using the MC prediction with the CMS FLUKA simulation of the detector and the cavern. The MC geometry used in the analysis describes very accurately the present RPC s…
View article: Collaborative Experience between Scientific Software Projects using\n Agile Scrum Development
Collaborative Experience between Scientific Software Projects using\n Agile Scrum Development Open
Developing sustainable software for the scientific community requires\nexpertise in software engineering and domain science. This can be challenging\ndue to the unique needs of scientific software, the insufficient resources for\nsoftware …
View article: Adaptive Multilevel Prediction Method for Dynamic Multimodal Optimization
Adaptive Multilevel Prediction Method for Dynamic Multimodal Optimization Open
This study develops an adaptive multilevel prediction (AMLP) method to detect and track multiple global optima over time. First, it formulates a multilevel prediction approach in which a higher level prediction improves the accuracy of the…
Quantum-Inspired Genetic Algorithm for Resource-Constrained Project-Scheduling Open
The Resource-Constrained Project-Scheduling Problem (RCPSP) is an NP-hard problem which can be found in many research domains. The optimal solution of the RCPSP problems requires a balance between exploration/exploitation and diversificati…
View article: A Hybrid Multi-Population Approach to the Project Portfolio Selection and Scheduling Problem for Future Force Design
A Hybrid Multi-Population Approach to the Project Portfolio Selection and Scheduling Problem for Future Force Design Open
Future Force Design (FFD) is a strategic planning activity that decides the programming of defence capability options. This is a complex problem faced by the Australian Department of Defence (DoD) and requires the simultaneous selection an…
View article: A Systematic Review of Coevolution in Real-Time Strategy Games
A Systematic Review of Coevolution in Real-Time Strategy Games Open
Real-time strategy (RTS) games are a subgenre of strategy video games. Due to their importance in practical decision-making and digital entertainment over the last two decades, many researchers have explored different algorithmic approache…
Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution Open
Shepherding involves herding a swarm of agents (\emph{sheep}) by another a control agent (\emph{sheepdog}) towards a goal. Multiple approaches have been documented in the literature to model this behaviour. In this paper, we present a modi…