This work presents a hybrid optimization framework for tackling cutting and packing problems, which is based upon a particular combination scheme between heuristic and exact methods. A metaheuristic engine works as a generator of reduced instances for the original optimization problem, which are formulated as mathematical programming models. These instances, in turn, are solved by an exact opti...

The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) metho...

Colliding Bodies Optimization (CBO) is a population-based metaheuristic algorithm that complies physics laws of momentum and energy. Due to the stagnation susceptibility of CBO by premature convergence and falling into local optima, some meritorious methodologies based on Sine Cosine Algorithm and a mutation operator were considered to mitigate the shortcomings mentioned earlier. Sine Cosine Al...

This paper introduces a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO), consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO method is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). The details of implementation for the multi-objective FJSP and the c...

Multi-agent systems are currently applied to solve complex problems. The security of networks is an eloquent example of a complex and difficult problem. A new model-concept Hybrid Sensitive Robot Metaheuristic for Intrusion Detection is introduced in the current paper. The proposed technique could be used with machine learning based intrusion detection techniques. The new model uses the reactio...

This paper describes a new metaheuristic for combinatorial optimisation problems with specific reference to the jobshop scheduling problem (JSP). A fuzzy greedy search algorithm (FGSA) which is a combination of a genetic algorithm (GA) and a greedy randomised adaptive search procedure (GRASP) is considered to solve the problem. The effectiveness and efficiency of the proposed hybrid method will...

This paper deals with the Permutation Flow Shop scheduling problem with the objective of minimizing total flow time, and therefore reducing in-process inventory. A new hybrid metaheuristic Genetic Algorithm Cluster Search is proposed for the scheduling problem solution. The performance of the proposed method is evaluated and results are compared with the best reported in the literature. Experim...