WP1: Data gathering

T1.1 Single-objective optimization data:

• GECCO results - You can download the results from the Genetic and Evolutionary Computation Conference (GECCO) competitions.
• CEC results- You can download the results from the IEEE Congres on Evolutionary Computation (IEEE CEC) competitions.
• Real-world optimization results - You can download the results for parameters estimation of biochemical systems.

T1.2 Multi-objective optimization data:

• DEMO results - You can download the results for the Difernetial Evolution for Multi-Objective Optimization Algorithm tested on DTLZ and WFG test problems.

T1.3 Pre-processing techniques for data management:

• Pre-processing functions - You can use parser functions developed for reading the data collected in WP1.

WP2: Methodologies for in-depth understanding of algorithms' performance

T2.1 Develop a methodology for practical significance

• pDSC - You can download the source code for practical Deep Statistical Comparison.

T2.2 Develop a methodology for multi-modal search

• eDSC - You can download the source code for extended Deep Statistical Comparison.

T2.3 Develop a methodology for multi-objective optimization

• To be announced...

T2.4 Develop a methodology for performance metrics fusion

• To be announced...

WP3: Validation using use cases

T3.1 Single-objective optimization

• Practical significance - You can find the valdiaiton results of pDSC.
• Multi-modal search - To be announced...
• Performance metrics fusion - To be announced...

T3.2 Multi-objective optimization

• Performance metrics fusion - You can find the valdiaiton results of performance metrics fusion for multi-objective optimization.

T3.3 Test cases from other research domains

• Natural Language Processing - To be announced...
• Biomedical Signal Processing - You can find the test case results for biomedical signal processing.
• Recommender Systems - You can find the test case results for evaluating recommender systems.

WP4: Framework for performing benchmarking analysis

T4.1 Design benchmark framework

• DSCTool - a web-service-based framework for statistical comparison of stochastic optimization algorithms.
• PerformViz - a machine learning approach to visualize and understand the performance of single-objective optimization algorithms.

T4.2 Development web services

• DSCTool web services documentation

T4.3 Implementation of framework

• R programming language clients

T4.4 Framework training

• Deep Statistics Tutorial
• DSCTool DEMO

WP5: Dissimenation, Communication and Outreach

T5.1 Website

T5.2 Scientific publications and conference activities

• More information about scientific publications and conference activities can be found in Publications and Events sections.

T5.3 Outreach

• To be announced...

T5.4 Communication activities

• Please follow us on our Twitter account: @JSI_CompSystems.

WP6: Project managmenet

T6.1 Project coordination

T6.2 Risk management

To be announced...