Hybrid metaheuristic algorithm

The proposed algorithm utilizes the migration method to identify local extremes and then relocates the population to explore new solution spaces for further evolution. The MIMEM algorithm is evaluated on the iMOPSE benchmark dataset, and the results demonstrate that it outperforms.

8p visystrom 22-11-2023 8 3   Download

This study suggests a new metaheuristic algorithm for global optimization, based on parallel hybridizing the swarm optimization (PSO) and Gravitational search algorithm (GSA). Subgroups of the population are formed by dividing the swarm’s community. Communication between the subsets can be developed by adding strategies for the mutation. Twenty-three benchmark functions are used to test its performance to verify the feasibility of the proposed algorithm.

11p linyanjun_2408 21-04-2022 19 3   Download

This paper develops a hybrid metaheuristic algorithm based on the Genetic Algorithm. In the developed algorithm, (1) a heuristic, (2) a local search, and (3) a restart phase is proposed.

24p tocectocec 24-05-2020 17 3   Download

This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries.

20p toritori 11-05-2020 9 1   Download

This study proposes a hybrid heuristic method based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic and the Clarke and Wright Savings algorithm, to solve a VRPLC with several loading and routing constraints that have not been considered simultaneously before. Experimental results show that the proposed procedure produces competitive solutions in short processing times. Lastly, the impact of the added operational constraints is also analyzed.

26p toritori 11-05-2020 14 1   Download

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 anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms.

11p trinhthamhodang1 16-11-2019 20 0   Download