We propose a new distributed and parallel meta-heuristic framework to address the issues of scalability and robustness in the optimization problem. The proposed framework, named PADO (Parallel And Distributed Optimization framework), can utilize heterogeneous computing and communication resources to achieve scalable speedup while maintaining high solution quality. Specifically, we combine an ex...

Training neural networks is a complex task that is important for supervised learning. A few metaheuristic optimization techniques have been applied to increase the effectiveness of the training process. The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. In this paper, Cuckoo search is implemented in...

In recent years, real-valued neural networks have demonstrated promising, and often striking, results across a broad range of domains. This has driven surge applications utilizing high-dimensional datasets. While many techniques exist to alleviate issues high-dimensionality, they all induce cost in terms network size or computational runtime. work examines the use quaternions, form hypercomplex...

This paper proposes a refined version of particle swarm optimization technique for the optimum design of steel structures. Swarm is composed of a number of particles and each particle in the swarm represents a candidate solution of the optimum design problem. Design constraints in accordance with ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution) are imposed by t...

in this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the p-mmrcpsp while due dates are included i...

In this chapter, an exhaustive survey of quantum behaved techniques on swarm intelligent is presented. The techniques have been categorized into different classes, and in conclusion, a comparison is made according to the benefits of the approaches taken for review. The above-mentioned techniques are classified based on the information they exploit, for instance, neural network related, meta-heu...

This paper investigates the development of an effective heuristic to solve the set covering problem (SCP) by applying the meta-heuristic Meta-RaPS (Meta-heuristic for Randomized Priority Search). In Meta-RaPS, a feasible solution is generated by introducing random factors into a construction method. Then the feasible solutions can be improved by an improvement heuristic. In addition to applying...

Meta-heuristic optimization algorithms are used in many application areas to solve problems. In recent years, meta-heuristic have gained importance over deterministic search solving However, none of the techniques equally effective all Therefore, researchers focused on either improving current or developing new ones. Many alternative inspired by nature been developed complex It is important com...