Meta-heuristic optimization algorithms have seen significant advancements due to their diverse applications in solving complex problems. However, no single algorithm can effectively solve all ...

Fuzzy optimization for shortest path problems addresses uncertainty in network weights by representing arc costs with fuzzy numbers rather than crisp values. By extending classical algorithms—such as ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...