Local search is a common method for solving combinatorial optimisation problems. We
focus on general-purpose local search solvers that accept as input a constraint model—a …

This paper presents Athanor, a novel local search solver that operates on abstract constraint
specifications of combinatorial problems in the Essence language. It is unique in that it …

Frequent itemset mining (FIM) is a method for finding regularities in transaction databases. It
has several application areas, such as market basket analysis, genome analysis, and drug …

Using constraint programming (CP) to explore a local-search neighbourhood was first tried
in the mid 1990s. The advantage is that constraint propagation can quickly rule out …

Neighborhood operators play a crucial role in defining effective Local Search solvers,
allowing one to limit the explored search space and prune the fitness landscape. Still, there …

Optimisation problems are crucial to both industry and society, and are problems where we
make decisions that optimise some objective while also satisfying some constraints. For …

Constraint Programming is the study of modelling and solving complex combinatorial
problems. Systematic-search and local-search are both well-researched approaches to …

Neighborhood operators play a crucial role in defining effective Local Search solvers,
allowing one to limit the explored search space and prune the fitness landscape. Still, there …

Combinatorial optimization problems are ubiquitous in real life and hence a wide range of
solving paradigms are available. Each paradigm has its own characteristics, which are …

This paper presents ATHANOR, a novel local search solver that operates on abstract
constraint specifications of combinatorial problems in the ESSENCE language. It is unique …