Foundational Concepts and Real-World Applications of Self-Adaptive Differential Evolution and Success History
Aleš Zamuda · IntechOpen eBooks · 2025
This chapter describes a range of foundational concepts in differential evolution (DE) algorithm, including distance-based success history differential evolution (DISH), and then tackles some challenges from real-world applications (RWAs) of DE. The DISH algorithm is described in more detail on how it self-adapts control parameters and how it is applied on evolutionary computation challenges, including recent 100-digit challenges. The chapter then continues with some RWA applications of self-adaptive DE by listing outcomes from benchmarks prepared in robotics, computer animation, energy, and document understanding, as well as other benchmarks from competitions on evolutionary computation. In robotics, a success history DE for underwater glider path planning is defined, in computer animation, a mixed-integer multi-objective optimization DE for tree geometry animation is listed, in energy, parallel constrained DE optimization for hydro-thermal scheduling, and in document understanding, a discrete constrained DE for text summarization. Main methods and results demonstrating their applicability are provided.