Definition 1.1 Global optimum. A solution s∗ ∈ S is a global optimum if it
has a better objective function4 than all solutions of the search space, that is,
∀s ∈ S, f (s∗) ≤ f (s).
Hence, the main goal in solving an optimization problem is to find a global optimal
solution s∗. Many global optimal solutions may exist for a given problem. Hence, to
get more alternatives, the problem may also be defined as finding all global optimal
solutions.
Different families of optimization models are used in practice to formulate and
solve decision-making problems (Fig. 1.2). The most successful models are based on
mathematical programming and constraint programming.
A commonly used model in mathematical programming is linear programming
(LP), which can be formulated as follows: