This paper presents a robust hybrid improved dolphin echolocation and ant colony optimization algorithm (IDEACO) for optimization of truss structures with discrete sizing variables. The dolphin echolocation (DE) is inspired by the navigation and hunting behavior of dolphins. An improved version of dolphin echolocation (IDE), as the main engine, is proposed and uses the positive attributes of an...

Several indicator-based evolutionary multiobjective optimization algorithms have been proposed in the literature. The notion of optimal μ-distributions formalizes the optimization goal of such algorithms: find a set of μ solutions that maximizes the underlying indicator among all sets with μ solutions. In particular for the often used hypervolume indicator, optimal μ-distributions have been the...

As most of the performance measures proposed for dynamic optimization algorithms in the literature are only for single objective problems, we propose new measures for dynamic multi-objective problems. Specifically, we give new measures for those problems in which the Pareto fronts are unknown. As these problems are the most common in the industry, our proposed measures constitute an important c...

Visualizing a high-dimensional solution set over the evolution process is a viable way to investigate the search behavior of evolutionary multi-objective optimization. The parallel coordinates plot which scales well to the data dimensionality is frequently used to observe solution sets in multi-objective optimization. However, the solution sets in parallel coordinates are typically presented by...

Wireless camera networks provide a unique opportunity for collaborative surveillance. Performance evaluation and optimization of camera networks, however, has seldom been addressed. This chapter fills this gap by detailing an approach by which individual cameras and a whole network of cameras can be simultaneously optimized in terms of Pareto efficiency using multi-objective optimization of per...

The influence of non-constant population sizes in evolutionary multi-objective optimization algorithms is investigated. In contrast to evolutionary single-objective optimization algorithms an increasing population size is considered beneficial when approaching the Pareto-front. Firstly, different deterministic schedules are tested, featuring different parameters like the initial population size...

This research paper is devoted to the study of the properties for Pareto-type efficient point sets in separated locally convex spaces, based upon an earlier result on the coincidence of Pareto-type efficient point sets and the Choquet boundaries and the natural corresponding extension for the approximate efficient point sets in Hausdorff locally convex spaces. Both of these results represent an...

We apply the concept of cost efficient claims to Lévy market models and find in an application to German stock prizes considerable potential savings the optimal payoffs provide. The magnitude of savings is related to the strength of the market trend. It is shown that the cost-efficient options also exhibit an improved behaviour concerning hedging errors. In the second part we introduce addition...