Due to its direct relevance to post-disaster operations, meter reading and civil refuse
collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important …

Evolutionary Algorithms (EAs) are inherently parallel due to their ability to simultaneously
evaluate the fitness of individuals. Synchronous Parallel EAs (SPEAs) leverage this with the …

Random graph generation techniques provide an invaluable tool for studying graph related
concepts. Unfortunately, traditional random graph models tend to produce artificial …

Optimal graph partitioning is a foundational problem in computer science, and appears in
many different applications. Multi-level graph partitioning is a state-of-the-art method of …

Many real-world engineering and science problems can be mapped to Boolean satisfiability
problems (SAT). CDCL SAT solvers are among the most efficient solvers. Previous work …

Successful applications of heuristic-based methods are able to find high-quality solutions for
complex problems in a feasible timeframe. However, they are usually tailored towards the …

The set of primitive operations available to a generative hyper-heuristic can have a dramatic
impact on the overall performance of the heuristic search in terms of efficiency and final …

• Implement five types of GP (tree GP, linear GP, canonical Cartesian GP, Stack GP, and
Grammatical Evolution) in hyper-heuristics for evolving black-box search algorithms for …

1. A search space contains the set of all possible solutions. 2. An objective function
determines the quality of solution. 3. A (Mathematical idealized) metaheuristic determines …

Dynamic primitive granularity control (DPGC) is a promising avenue for improving the
performance of genetic programming (GP). However, it remains almost entirely unexplored …