Multi-Objective Optimization for Decision Support and Risk Assessment in Maritime Asset Allocation Problems

In many maritime applications minimizing a risk function alone can be ineffective in accurately modeling the problem at hand. As a matter of fact, most of the engineering applications require the concurrent optimization of multiple objectives, in order to obtain a meaningful trade-off solution. After discussing the state-of-the-art in solving Lexicographic Multi- Objective Linear Programming (LMOLP) problems, we will present an efficient way to solve them, which has been recently proposed in literature [1]. Such an efficient LMLP solver is crucial to solve the Multi-Objective Weapon-Target Assignment problem (MOWTA)[2- 3]. The MOWTA problem, on its turn, is a powerful metaphor that can be used in several maritime applications, such as: i) to decide where to direct underwater gliders in order to maximize the information gathered and to minimize the risk of losing them (especially when they are used in denied areas); ii) to decide where to direct patrolling vessels to contrast illegal immigration in the Mediterranean sea.