دانلود کتاب مقایسه عمیق آماری برای الگوریتم‌های بهینه‌سازی تصادفی فراابتکاری

Optimization is finding the best solution from among all the feasible solutions. In mathematics and computer science, this challenging task is being tackled by many researchers around theworldwhoare inventing various approaches and algorithms. In the past 20 years, the inventing of newoptimization algorithms has become something of a competition, not only with oneself, but also with other researchers. In theory, competitive activities have many benefits and help researchers develop important skills, like perseverance and resilience, as well as protecting science from stagnation. However, to avoid unfair competition, clear rules need to be defined and agreed on when comparing the approaches and algorithms. Tome Eftimov and Peter Korošec are that rare breed of computer scientist that recognize the need to define the rules for benchmarking algorithms in a specific field ofmeta-heuristic stochastic optimisation. They provide a fascinating compendium of theoretical and practical guides and even a web-based tool formaking a statistical comparison of both single-objective and multiobjective optimisation algorithms in a fair way. This book provides a path forward, not only in the field of meta-heuristic stochastic optimisation, but also in other fields of computer science where approaches and algorithms should be benchmarked in the correct way before announcing them as the best solutions. As a consequence, the researcher who wins the competition will succeed as a true scientist, which is the most beautiful feeling of all.