Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Abstract: Several optimization problems from various types of applications have been efficiently resolved using available meta-heuristic algorithms such as Particle Swarm Optimization and Genetic ...

The area of approximation algorithms is aimed at giving provable guarantees on the performance of heuristics for hard problems. The course will present general techniques (such as convex ...

Abstract: A constructive heuristic algorithm (CHA) to solve distribution system planning (DSP) problem is presented. The DSP is a very complex mixed binary nonlinear programming problem. A CHA is ...

A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...

Particle swarm optimization (PSO) algorithm is an optimization technique with remarkable performance for problem solving. The convergence analysis of the method is still in research. This article ...

In this mini-review, we introduce and summarize research from the Quantum Technologies Group (QTG) at Carnegie Mellon University related to computational experience with quantum annealing, performed ...

Edit distance—a classical problem in computer science—has received ongoing attention from both practitioners and theoreticians. Given two strings A and B, the edit distance is the minimum number of ...

Developing faster algorithms is an important but elusive goal for data scientists. The ability to accelerate complex computing tasks and reduce latency has far-reaching ramifications in areas such as ...