Metaheuristics for Logistics

9Hybridization and Coupling Using Metaheuristics

In this last chapter dedicated to metaheuristics, we will describe two advanced techniques called metaheuristics-based hybridization and coupling. We shall begin by pointing out the benefits that these techniques can bring for dealing with problems of optimization related to supply chain management, before going into the details.

9.1. Metaheuristics for the optimization of the supply chain

In order to optimize the functioning of the supply chain, it is necessary to overcome many difficulties:

• – Model the supply chain: the diverse entities (actors, activities, products, sites) that take part in the supply chain must be defined, as well as their interactions. The development of the knowledge-based model is often a consuming and cumbersome task.
• – Overcome algorithm complexity: theoretical problems, like those we have worked with so far, are not polynomials and, therefore, difficult to solve. We must take into account two factors that make real problems even more difficult than academic problems. On the one hand, real problems often lead to instances where big size issues must be solved. On the other hand, real problems integrate management rules or specific constraints that must be taken into account.
• – Overcome structural complexity: ask an industrialist to specify the criteria that enables him to judge if his system is efficient. Performance criteria of a supply chain are most often based on the minimization of expenses and ...