While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
Currently, among the fastest approaches to AI task planning we find many forward-chaining heuristic planners, as FF. Most of their good performance comes from the use of domain-i...
In the past several years, significant progress has been made in finding optimal solutions to combinatorial problems. In particular, random instances of both Rubik's Cube, wi...
The barycenter heuristic is often used to solve the NP-hard two-layer edge crossing minimization problem. It is well-known that the barycenter heuristic can give solutions as bad a...
This paper presents a novel evolutionary approach to solve numerical optimization problems, called Adaptive Evolution (AEv). AEv is a new micro-population-like technique because i...