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Ripon Kumar Chakrabortty

Ripon Kumar Chakrabortty
UNSW Canberra · School of Systems & Computing

PhD in Computer Science
Team Leader and Founder for "Decision Support & Analytics Research Group". Link: https://www.unsw.adfa.edu.au/dsar-group

About

267
Publications
163,578
Reads
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7,110
Citations
Additional affiliations
November 2018 - November 2018
UNSW Canberra
Position
  • Lecturer
August 2013 - present
UNSW Sydney
Position
  • PhD Student
August 2013 - present
Rajshahi University of Engineering and Technology
Position
  • Lecturer
Education
August 2013 - March 2017
University of New South Wales, Canberra, Australia
Field of study
  • Project Management

Publications

Publications (267)
Article
In this paper, we consider Resource Constrained Project Scheduling Problems (RCPSPs) with known deterministic renewable resource requirements but uncertain activity durations. In this case, the activity durations are represented by random variables with different probability distribution functions. To deal with this problem, we propose an approach...
Thesis
Full-text available
The resource constrained project scheduling problem (RCPSP) has been an important research topic over the past few decades, mainly because of its applicability to many real-world situations. Over the last few decades, research on resource constrained project scheduling has focused on the development of mathematical programming based approaches for...
Article
This paper aims to identify an efficient priority rule (PR) for resource constrained project scheduling problems under dynamic environments. Here the dynamicity comes from the unstable resource availability, time-varying resource demands and stochastic activity durations for each of the project activities. This extended dynamic project scheduling p...
Article
The Resource Constrained Project Scheduling Problem (RCPSP) is a combinatorial optimization problem whichis non-deterministic polynomial-time (NP)-hard in nature. Due to the diversified applications of RCPSPs, theyhave been commonly used as scheduling procedures in real-world problems. Since, in practice, project data areprone to changes or disrupt...
Article
Full-text available
Manufacturing supply chains (SC) shift from traditional make-to-stock systems to make-to-order (MTO) systems in order to coordinate the production and distribution of complex and highly customized products. Despite the need for advanced scheduling approaches when coordinating such MTO-based SCs, there is little research focussing on practical setti...
Article
Full-text available
The efficacy of feed-forward multi-layer neural networks relies heavily on their training procedure, where identifying appropriate weights and biases plays a pivotal role. Nonetheless, conventional training algorithms such as backpropagation encounter limitations, including getting trapped in sub-optimal solutions. To rectify these inadequacies, me...
Conference Paper
Full-text available
Machine learning (ML) has become integral in numerous industries, offering unparalleled data analysis, pattern recognition, and predictive modelling advantages. However, the opacity of ML models, often referred to as "black boxes," poses significant challenges in understanding their decision-making processes. Explainable Artificial Intelligence (XA...
Article
Full-text available
Locating a set of influential users within a social network, known as the Influence Maximization (IM) problem, can have significant implications for boosting the spread of positive information/news and curbing the spread of negative elements such as misinformation and disease. However, the traditional simulation‐based spread computations under conv...
Chapter
The current global market’s fierce competition, coupled with shortened product life cycles and elevated customer demands, has prompted organizations to give precedence to sustainable supply chain management. Yet, factors like political challenges, fluctuations in demand, technological advancements, financial instability, and natural calamities have...
Poster
Full-text available
Overview and Scope Partitioning points out techniques in which the samples are divided into different groups in terms of some criteria. Clustering is a special type of partitioning approach in which the samples are categorised into a group according to their similarities. Partitioning can be applied for different purposes in evolutionary computatio...
Article
Preventive and corrective maintenance-workforce planning for assets is a growing area of research, given the presence of uncertainty. We model a Simulation-Optimization framework to solve this challenging large-scale maintenance-workforce planning problem while considering its stochastic nature inside both the simulation and optimization models. A...
Article
Full-text available
Biofuel supply chains (BSCs) face diverse uncertainties that pose serious challenges. This has led to an expanding body of research focused on studying these challenges. Hence, there is a growing need for a comprehensive review that summarizes the current studies, identifies their limitations, and provides essential advancements to support scholars...
Article
Feature selection is the most significant pre-processing activity, which intends to reduce the data dimensionality for enhancing the machine learning process. The evaluation of feature selection must consider classification, performance, efficiency, stability, and many factors. Nowadays, uncertainty is commonly occurred in the feature selection pro...
Article
Full-text available
The growing interest in blockchain technology has gained a lot of attention in Supply Chain Management (SCM) and sparked the quest for decentralized, scalable, efficient and trustworthy consensus schemes. Traditional blockchains rely on computationally expensive consensus mechanisms with low throughput and high latency. This paper conducts a perfor...
Article
Full-text available
The proper trade-off between various project costs is often disregarded when planning projects. This leads to several detrimental effects, such as inaccurate planning and higher total cost, far more significant in a multi-project environment. To overcome this limitation, this study proposes a combined approach for the multi-project scheduling and m...
Article
Full-text available
Conventionally, project managers schedule the activities first; later prepare for materials management, procurement, and supplier selection in project planning. This disjointed process leads in a loss of expected profit for the company owing to a lack of planning coordination. In this paper, a mixed integer programming model is developed for resour...
Chapter
Supply Chain Risk Management (SCRM) is necessary for economic development and the well-being of society. Therefore, many researchers and practitioners focus on developing new methods to identify, assess, mitigate and monitor supply chain risks. This paper developed the Risk Management by Counterfactual Explanation (RMCE) framework to manage risks i...
Article
Full-text available
The primary goal of this research paper is to develop a tool for screening for Asperger Syndrome (AS). The “multi-criteria decision-making (MCDM)” method, an extensively used approach for making decisions involving several criteria, has been used to create this screening tool. The amount of knowledge available to a person is vast, ambiguous, and un...
Article
Uncertainty is ubiquitous in almost every real-life optimization problem, which must be effectively managed to get a robust outcome. This is also true for the Influence Maximization (IM) problem, which entails locating a set of influential users within a social network. However, most of the existing IM approaches have overlooked the uncertain facto...
Article
Full-text available
Modular product family architecture (PFA), in coordination with the supply chain, assists manufacturers in achieving lower costs and higher efficiency by sharing a common platform. Despite its advantages, however, the prevailing practice of PFA emphasises architectural aspects that do not focus on the interface requirements for an efficient supply...
Article
Full-text available
Lithium-ion battery (LiB), a leading residual energy resource for electric vehicles (EVs), involves a market presenting exponential growth with increasing global impetus towards electric mobility. To promote the sustainability perspective of the EVs industry, this paper introduces a hybridized decision support system to select the suitable location...
Article
The five papers in this special section focus on the impact to supply chain management in a post-COVID pandemic era, with emphasis on the applications on artificial intelligent technologies for the emerging Fifth Industrial Revolution (Industry 5.0).
Article
Full-text available
This study presents a novel hybrid framework combining feature selection, oversampling, and machine learning (ML) to improve the prediction performance of vehicle insurance. The framework addresses the class imbalance problem in binary classification tasks by employing principal component analysis for feature selection, the synthetic minority overs...
Article
Full-text available
This paper proposes a novel framework to improve the prediction accuracy of very short-term (5-min) wind power generation. The framework consists of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), monarch butterfly optimization (MBO) and long short-term memory (LSTM), called CEMOLS. The CEEMDAN is employed to extract c...
Article
The ongoing COVID-19 pandemic has created an unprecedented predicament for the global supply chains (SCs). Shipments of essential and life-saving products, ranging from pharmaceuticals, agriculture, healthcare, to manufacturing, have been significantly impacted or delayed, making the global SCs vulnerable. A better understanding of the shipment ris...
Article
Decision support systems (DSS) assist in a wide array of decision-making tasks in different domains. However, one of their common drawbacks is that their working is back box in nature. This means that while they recommend a decision, they cannot explain the ’why’ behind reaching that decision. In prescriptive tasks such as risk management, this doe...
Article
Full-text available
In product family design (PFD), deciding on a platform design strategy can be viewed as a multidisciplinary optimization problem that involves several factors, such as design variables, manufacturing costs, customizability, supplier reliability, and customer satisfaction. In this study, a multi-objective based differential evolution (MO-based DE) a...
Article
Building simulation models that are valid and credible is an enduring challenge in the Australian Defence Organisation (ADO) context. Establishing validity and credibility can be achieved through the rigorous use of appropriate Verification, Validation, and Accreditation (VVA) processes. Such processes are well-known in modeling and simulation (M&S...
Conference Paper
Identification of a set of influential spreaders in a network, called the Influence Maximization (IM) problem, has gained much popularity due to its immense practicality. In real-life applications, not only the influence spread size, but also some other criteria such as the selection cost and the size of the seed set play an important role in selec...
Article
Make-to-order (MTO) or engineer-to-order (ETO) systems produce complex and highly customized products and, therefore, there is a need for advanced project scheduling ap- proaches for production planning in these systems. An important aspect of production scheduling is the assignment of operators with specific human factors to activities in a manufa...
Article
Maintenance of Australian hospitals’ Critical Medical Devices (CMDs) can be somewhat more demanding than conventional assets from other industries. This is primarily driven by the requirement for CMDs to operate with exceptional levels of reliability. This study proposes a combined Reliability Centred Maintenance (RCM) and prioritisation maintenanc...
Article
Military capability acquisition and enhancement is a strategic issue that can significantly impact national security. The present study identifies the gaps and provides additional research into the application of Multi-Criteria Decision Making (MCDM). Current research within literature predominantly investigates developments, modifications, and eva...
Chapter
The resource constrained multi-project scheduling problem (RCMPSP) is a well-known NP-hard problem. In this study, a surrogate- assisted genetic algorithm (SaGA) is presented for solving the RCMPSP. A non-random initialization starts the SaGA with a certain diversity and quality. A forward-backward improvement (FBI) based local search is utilized t...
Article
Full-text available
This paper introduces a novel physical-inspired metaheuristic algorithm called “Light Spectrum Optimizer (LSO)” for continuous optimization problems. The inspiration for the proposed algorithm is the light dispersions with different angles while passing through rain droplets, causing the meteorological phenomenon of the colorful rainbow spectrum. I...
Article
The upsurge of the COVID-19 pandemic and its consequences on the world’s population has led to the accelerated production of vaccines across the world. The next challenge in the fight against COVID-19 is to distribute those vaccines to the right person in an optimized way by establishing an efficient vaccine supply network. Consequently, this paper...
Article
A vaccination campaign is one of the most important initiatives to return life to normal in the face of the current COVID-19 epidemic. A successful immunisation programme requires optimising the strategy since uncertainty and disruptions play a role in the decision-making process. Despite the significance of this issue in practical terms, little re...
Chapter
One of the most challenging issues that humans face in the last decade is in the health sector, and it is threatening his existence. The COVID-19 is one of those health threats as declared by the World Health Organization (WHO). This spread of COVID-19 forced WHO to declare this virus as a pandemic in 2019. In this paper, COVID-19 chest X-rays clas...
Article
Full-text available
In supply chain literature, production coordination and vehicle routing have received a lot ofattention. Even though all functions in the supply chain are interrelated, they are normally handledindependently. This disconnected approach might lead to less-than-ideal outcomes. Increasing totalefficiency by integrating manufacturing and delivery sched...
Article
Knowledge of influential actors on real networks is essential for designing policies for boosting the spread of positive things (e.g., news and innovation) and preventing the spread of negative things (e.g., disease and misinformation). Finding an optimum set of nodes with maximum influence, known as Influence Maximization (IM), aims to achieve thi...
Article
The profitability of a supply chain (SC) is proportional to the stability of all its stakeholders as well as their consistent information sharing with an effective and efficient communication mechanism. Various inefficiencies, such as bullwhip effect (BWE) and product unavailability, may be caused by lack of coordination in a SC. The importance of...
Article
The COVID-19 pandemic has created multiple problems in the existing transportation system. The contribution of this study is to guide logistics managers as they make ordering decisions within a disrupted transportation system. In the overall supply chain system, inventory decisions have been either compromised or challenged. Traditional inventory d...
Article
Full-text available
COVID-19's fast spread in 2020 compelled the World Health Organization (WHO) to declare COVID-19 a worldwide pandemic. According to the WHO, one of the preventative countermeasures against this type of virus is to use face masks in public places. This paper proposes a face mask detection model by extracting features based on the neutrosophic RGB wi...
Article
Full-text available
This study involves an optimum balance between ordering cost reduction and product deterioration in controllable carbon emissions for a sustainable green warehouse. The sensitivity analysis is to simulate the impact of those attributes. Industries are foraging to find a proper balance between the use of fossil fuels and reducing carbon emissions, a...
Article
The COVID-19 pandemic has cast a shadow on the global economy. Since the beginning of 2020, the pandemic has contributed significantly to the global recession. In addition to the health damages of the pandemic, the economic impacts are also severe. The consequences of such effects have pushed global supply chains toward their breaking point. Indust...
Article
Recent global changes have prompted manufacturers to shift their production systems to make-to-order (MTO) supply chain (SC), enabling them to adapt customised customer requirements with their rapidly changing behaviours, reduce inventory costs, and obtain competitive advantages in the market. However, traditional MTO-based scheduling approaches fa...
Article
Full-text available
This study introduces an integrated decision-making methodology to choose the best “waste-to-energy (WTE)” technology for “municipal solid waste (MSW)” treatment under the “interval-valued Pythagorean fuzzy sets (IPFSs)”. In this line, first, a new similarity measure is developed for IPFSs. To show the utility of the developed similarity measure, a...