The main aim of the present study is to optimize steel moment frames in the framework of performance-based design and to assess the seismic collapse capacity of the optimal structures. In the first phase of this study, four well-known metaheuristic algorithms are employed to achieve the optimization task. In the second phase, the seismic collapse safety of the obtained optimal designs is evalua...

Problems for which many objective functions are to be simultaneously optimised are widely encountered in science and industry. These multiobjective problems have also been the subject of intensive investigation and development recently for metaheuristic search algorithms such as ant colony optimisation, particle swarm optimisation and extremal optimisation. In this chapter, a unifying framework...

This paper proposes a visualization tool for analyzing the behavior of metaheuristic algorithms. It works by reproducing graphically the solutions generated in execution time. The tool was evaluated analyzing the Hybrid Grouping Genetic Algorithm for Bin Packing (HGGA_BP). It was used to solve a benchmark with 17 instances of the one dimensional Bin Packing problem (1D-BPP). The use of the visu...

This paper addresses the multistage hybrid flow shop (HFS) scheduling problems. The HFS is the special case of flowshop problem. Multiple parallel machines are considered in each stage in the HFS. The HFS scheduling problem is known to be strongly NPhard. Hence, many researchers proposed metaheuristic algorithms for solving the HFS scheduling problems. This paper develops a bat algorithm (BA) t...

Ant programming is a kind of automatic programming that generates computer programs by using the ant colony metaheuristic as the search technique. It has demonstrated good generalization ability for the extraction of comprehensible classifiers. To date, three ant programming algorithms for classification rule mining have been proposed in the literature: two of them are devoted to regular classi...

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomal...

When assessing experimentally the performance of metaheuristic algorithms on a set of hard instances of an NP-complete problem, the required time to carry out the experimentation can be very large. A means to reduce the needed effort is to incorporate variance reduction techniques in the computational experiments. For the incorporartion of these techniques, the traditional approaches propose me...