Hybrid meta-heuristic machine learning methods applied to landslide susceptibility mapping in the Sahel-AlgiersArtificial neural networkHybrid metaheuristic optimization algorithmsLandslide susceptibilityGeographical information systemSensitivity analysisLandslides are considered as one among many phenomena jeopardizing ...
Also, the meta-heuristic algorithm should escape from the local optimum. In literature, there are meta-heuristic algorithms, such as, Particle Swarm Optimization (PSO) and Cuckoo Search that aim at global optimization (Exploration) and algorithms like Simulated Annealing (SA) and Harmony Search ...
Hence, a meta-heuristic algorithm is what required in reaching the optimal response. Thus, the algorithm is a hybridization of the ant lion optimizer (ALO) algorithm with a Sine Cosine Algorithm (SCA) algorithm and used it multi-objectively to solve the problem of scheduling scientific workflows...
This paper presents a novel hybrid meta-heuristic algorithm called HMGSG to solve the optimization problems. In the proposed HMGSG algorithm, a spiral-shaped path for grey wolf optimization (GWO) is used to ensure both the faster convergence rate and diversity. The mutualism phase of symbiotic ...
HMOSHSSA: a hybrid meta-heuristic approach for solving constrained optimization problemsMulti-objective optimizationHMOSHSSASpotted Hyena OptimizerSalp Swarm AlgorithmConstrained optimizationEngineering design problemsThis paper proposes a novel hybrid multi-objective optimization algorithm named HMOSHSSA by ...
Hybrid Meta-Heuristic based Optimization for Multi-constrained Quality of Service Routing in MANETsIn MANET, designing a dynamic routing algorithm by satisfying QoS requirement is a challenging task. Multi-constrained QoS routing aims to optimize multiple QoS metrics while provisioning required network ...
This improved approach enables the particle swarm algorithm to be equipped with fast convergence of performance. (3) The initialization of the swarm. Alsaidy and Abbood proposed27 a hybrid task scheduling algorithm that replaced the random initialization of the meta-heuristic algorithm with the ...
Comparative analysis of some evolutionary-based models in optimization of dam reservoirs operation Article Open access 02 August 2021 Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique Article Open access 28 April 2023...
In this paper, two new hybrid metaheuristic Differential Evolution (DE) and Particle Swarm Optimization algorithm (PSO) (denoted by DPD) for solving engineering design problems has been developed. This hybrid algorithm is designed to improve the efficiency of the DE and PSO and remove some of the...
A hybrid meta-heuristic algorithm, which was based on adaptive simulated annealing (ASA), was proposed in [12] to solve the nonconvex ED problem. Adeyanju and Canha proposed a select meta-heuristic optimization (MO) algorithm to solve the decentralized multi-area multi-agent ED problem taking ...