Track-oriented multiple hypothesis tracking (MHT) is well-established as a paradigm for multi-sensor multitarget tracking. The fundamental approach includes many variants. Hypothesis-oriented MHT was first proposed by Reid [10]. The initial integer-programming formulation of the problem is due to Morefield [8]. The hybrid-state decomposition that allows for computationally-efficient track-orien...

In general, Multi-objective Evolutionary Algorithms do not guarantee find solutions in the Pareto-optimal set. We propose a new approach for solving decomposable deceptive multi-objective problems that can find all solutions of the Pareto-optimal set. Basically, the proposed approach starts by decomposing the problem into subproblems and, then, combining the found solutions. The resultant appro...

Most of the derivative-free optimization (DFO) algorithms rely on a comparison function able to compare any pair of points with respect to a blackbox objective function. Recently, new dedicated derivative-free optimization algorithms have emerged to tackle multi-objective optimization problems and provide a Pareto front approximation to the user. This work aims at reusing single objective DFO a...

In this paper, we propose and analyze two schemes to integrate an objective reduction technique into a multi-objective evolutionary algorithm (MOEA) in order to cope with many-objective problems. One scheme reduces periodically the number objectives during the search until the required objective subset size has been reached and, towards the end of the search, the original objective set is used ...

When facing a real world, optimization problems mainly become multiobjective i.e. they have several criteria of excellence. A multi-criteria problem submitted for multi-criteria evaluation is a complex problem, as usually there is no optimal solution, and no alternative is the best one according to all criteria. However, if a metaheuristic algorithm is combined with a Multi-Criteria Decision-Ma...

I shall argue that there is no such property of an event as its “probability.” This is why standard interpretations cannot give a sound definition in empirical terms of what “probability” is, and this is why empirical sciences like physics can manage without such a definition. “Probability” is a collective term, the meaning of which varies from context to context: it means different—dimensionle...