Decomposition-based optimization involves transforming a complex problem into multiple smaller, more manageable sub-problems that can be solved cooperatively. The evolutionary computing community actively develops methods to explicitly or implicitly design decomposition across four key facets: (i) environmental parameters, (ii) decision variables, (iii) objective functions, and (iv) available computing resources.

This workshop aims to bring together recent advances in the design, analysis, and understanding of evolutionary decomposition techniques. It also provides a platform to discuss challenges in applying decomposition to increasingly large and complex optimization tasks—such as problems with many variables or objectives, multi-modal problems, simulation-based optimization, and uncertain scenarios—while considering modern large-scale computing environments, including massively parallel and decentralized systems.

The workshop focuses on, but is not limited to, the following topics:

• Large-scale evolutionary decomposition: Decomposition in decision space, gray-box methods, co-evolutionary algorithms, grouping techniques, and cooperative methods for constraint handling.
• Many- and multi-objective decomposition: Aggregation and scalarization methods, hybrid island-based approaches, and (sub-)population decomposition and mapping.
• Parallel and distributed evolutionary decomposition: Scalability across decision and objective spaces, decentralized divide-and-conquer strategies, distributed computing efforts, and deployment on heterogeneous, large-scale parallel platforms.
• New general-purpose decomposition techniques: Machine-learning-assisted decomposition, online and offline configuration, search region decomposition, use of multiple surrogates, and parallel approaches for expensive optimization.
• Emerging applications of evolutionary techniques based on decomposition.
• Understanding and benchmarking decomposition techniques.
• Software tools and libraries for evolutionary decomposition.

In general, this workshop encourages both theoretical and practical contributions, focusing on developmental, implementation, and applied aspects of decomposition techniques in evolutionary optimization.