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DSARG datasets

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One important aspect of any research is to validate results. Each of our research works is carefully crafted to adapt the problem-in-hand, followed by proper solution mechanisms. Results produced from our research works are (usually) validated against benchmark datasets and/or state-of-the-art approaches. However, occasionally when there is no existing benchmark dataset to validate our proposed models, we create our own dataset with the best-informed scenario. Each of our created datasets, their corresponding results and codes for each solution mechanism are archived on this publicly accessible page. Future researchers are encouraged to use our proposed dataset to validate their method. They can even use our publicly accessible codes. All these datasets are also linked with their respective journal/conference article.

Number Dataset name Overview
1 All simulated datasets can be achieved from this link, while project data are considered as dynamic (activity durations, resource demands, and resource usage)
2 Data for disruption scenarios can be obtained from this link. This work is published as 'Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach' in theÌýIEEE AccessÌýÂá´Ç³Ü°ù²Ô²¹±ô.
3 All relevant datasets for executing task scheduling in fog-cloud computing environments.
4 All relevant results of IGA the classical NPV-based RCPSP. This work is published as 'An Immune Genetic Algorithm for Solving NPV-Based Resource Constrained Project Scheduling Problem' in theÌýIEEE AccessÌýÂá´Ç³Ü°ù²Ô²¹±ô.
5 The newly created dataset for GRCPSPM (Green RCPSP for Manufacturing). This paper is currently under consideration in theÌýEuropean Journal of Operational Research.
Ìý This work is published as 'An Event-Based Reactive Scheduling Approach for the Resource Constrained Project Scheduling Problem with Unreliable Resources' in theÌýComputers & Industrial EngineeringÌýJournal.
7 All datasets and relevant results for the 'Multi-Project Scheduling and Material Ordering Problem with Environmental and Quality Reflections' paper. Details about those datasets are placed in the manuscript (e.g., readme. file).
8 All datasets and relevant results for the 'Resource-Constrained Project Scheduling and Material Ordering Problem with Discounted Cash Flows' paper. Details about those datasets are placed in the manuscript (e.g., readme. file).
9 All datasets and a readme file for the paper titled 'Bi-Objective Supply Chain Scheduling Problem with Supplier Selection and Customer-Imposed Delivery Time Window', which has been submitted to theÌýComputers & Industrial EngineeringÌýÂá´Ç³Ü°ù²Ô²¹±ô.
10 Relevant datasets for the work under review titled 'A Blockchain-Coordinated Supply Chain to Minimise Bullwhip Effect with an Enhanced Trust Consensus Algorithm'. This paper has been submitted as a possible publication in theÌýComputers & Industrial EngineeringÌýÂá´Ç³Ü°ù²Ô²¹±ô.
11 Self-generated datasets for the work under review titled 'Manufacturing Project Scheduling Considering Human Factors to Minimise Total Cost and Carbon Footprints'. This paper has been submitted as a possible publication in theÌýExpert Systems with ApplicationsÌýÂá´Ç³Ü°ù²Ô²¹±ô.
12 Self-generated datasets for the work under review titled 'Synchronisation of Permutation Flow Shop Scheduling Considering Sequence Dependent Setup Time and Batch Delivery to Multiple Customers in Supply Chain'. This paper has been submitted for a possible publication.
13 Results of the 'Multi-Operator Immune Genetic Algorithm for Project Scheduling with Discounted Cash Flows' paper. This paper has been published in theÌýComputers & Industrial EngineeringÌýÂá´Ç³Ü°ù²Ô²¹±ô.Ìý
Ìý Excel data file and supporting dataset for the work on 'Dynamic Modelling for Product Family Evolution Combined with Artificial Neural Network Based Forecasting Model'. This work has been submitted in theÌýTechnological Forecasting & Social ChangeÌýÂá´Ç³Ü°ù²Ô²¹±ô.
15 The Excel Dataset for the module-based product family design. This work has been submitted inÌýComputers & Industrial EngineeringÌýwith the title 'An Integrated Differential Evolution Algorithm for Module-based Product Family Design'.
16 Dataset and Excel results for the work titled 'Designing an Efficient Vaccine Supply Chain Network Using a Two-Phase Optimisation Approach: A Case Study of COVID-19 Vaccine'.Ìý
17 Dataset for the 'Dynamic Modeling for Product Family Evolution: MABAC and ANN Focused' paper. This paper has been in the 2nd review inÌýExpert Systems with ApplicationsÌýÂá´Ç³Ü°ù²Ô²¹±ô.Ìý
18 Dataset for the "Optimizing Vaccines Supply Chains to Mitigate the COVID-19 Pandemic' paper. This work has been submitted toÌýInternational Journal of Systems Science: Operations & Logistics.
19 Dataset for the work titled 'A self-Adaptive Hyper-heuristic Based Multi-Objective Optimization Approach for Integrated Supply Chain Scheduling Problems'. This paper has been submitted toÌýEuropean Journal of Operational Research.

Key contact

Dr Ripon K. Chakrabortty
M: +61 414 388 209
E:Ìýr.chakrabortty@unsw.edu.au