Most real-world optimization problems are multiobjective by nature, involving
noncomparable objectives. Many of these problems can be formulated in terms of a set of …

Branch and bound is a well-known generic method for computing an optimal solution of a
single-objective optimization problem. Based on the idea “divide to conquer”, it consists in …

In this chapter we consider multi-objective optimisation problems with a combinatorial
structure. Such problems have a discrete feasible set and can be formulated as integer …

Automatic evaluation of human facial attractiveness is a challenging problem that has
received relatively little attention from the computer vision community. Previous work in this …

Fixed Point Theory, Variational Analysis, and Optimization not only covers three vital
branches of nonlinear analysis—fixed point theory, variational inequalities, and vector …

Well-suited to embarrassingly parallel applications, the master–worker (MW) paradigm has
largely and successfully used in parallel distributed computing. Nevertheless, such a …

Solving to optimality large instances of combinatorial optimization problems using Brand
and Bound (B&B) algorithms requires a huge amount of computing resources. In this paper …

Solving optimally large instances of combinatorial optimisation problems using Branch and
Bound (B&B) algorithms is CPU-time intensive and requires a large number of …

Branch and Bound (B&B) algorithms are efficiently used for exact resolution of combinatorial
optimization problems (COPs). They are easy to parallelize using the Master/Worker …

A p-star is a complete bipartite graph K 1, p with one center node and p leaves. In this paper,
we propose a polynomial self-stabilizing algorithm for maximal graph decomposition into p …