Hyper-heuristics aim at interchanging different solvers while solving a problem. The idea is
to determine the best approach for solving a problem at its current state. This way, every time …

The main idea of constraint programming (CP) is to determine a solution (or solutions) of a
problem assigning values to decision variables satisfying all constraints. Two sub …

Constraint programming is an efficient and powerful paradigm for solving constraint
satisfaction and optimization problems. Under this paradigm, problems are modeled as a …

Abstract In Constraint Programming, enumeration strategies play an important role, they can
significantly impact the performance of the solving process. However, choosing the right …

Many of the works conducted on algorithm selection strategies—methods that choose a
suitable solving method for a particular problem—start from scratch since only a few …

Selection hyper-heuristics are a technology for optimization in which a high-level
mechanism controls low-level heuristics, so as to be capable of solving a wide range of …

In this paper, we present a new Artificial Bee Colony algorithm to solve the non-unicost Set
Covering Problem. The Artificial Bee Colony algorithm is a recent metaheuristic technique …

Constraint Programming is a powerful paradigm which allows the resolution of many
complex problems, such as scheduling, planning, and configuration. These problems are …

Intelligent Hyper-heuristics: A Tool for Solving Generic Optimisation Problems Page 1
Intelligent Hyper-heuristics: A Tool for Solving Generic Optimisation Problems Mustafa Mısır …

Solving constraint satisfaction problems via constraint programming involves the exploration
of a search tree where the potential solutions are distributed. The exploration phase is …