Name
Title | ||
|---|---|---|
Recent advances in multi-objective grey wolf optimizer, its versions and applications |
Abstract | ||
|---|---|---|
In this work, a comprehensive review of the multi-objective grey wolf optimizer (MOGWO) is provided. In multi-objective optimization (MO), more than one objective function must be considered at the same time. To deal with such problems, a priori or a posteriori MOGWO variants have been proposed in the literature. In the a priori model, the multi-objective functions are aggregated into a single objective function by a number of weights. In the posterior model, the multi-objective formulation is maintained and MOGWO is employed to estimate the Pareto optimal solutions representing the best trade-offs between the objectives. Due to the successful performance of MOGWO, it has been widely utilized for MO. This review covers the research growth of MOGWO in terms of a number of researches, topics, top researchers, etc. Furthermore, several versions of MOGWO have been introduced and reviewed with applications in diverse fields. This work also provides a critical analysis to show the shortcomings and limitations of using the basic version of MOGWO followed by several future directions. This review paper will be a base paper for any researcher interested to implement MOGWO in its work. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s00521-022-07704-5 | NEURAL COMPUTING & APPLICATIONS |
Keywords | DocType | Volume |
Multi-objective grey wolf optimizer, Multi-objective optimization, Metaheuristics | Journal | 34 |
Issue | ISSN | Citations |
22 | 0941-0643 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sharif Naser Makhadmeh | 1 | 0 | 0.34 |
| Osama Ahmad Alomari | 2 | 5 | 1.81 |
| Seyedali Mirjalili | 3 | 3949 | 140.80 |
| Mohammed Azmi Al-Betar | 4 | 1 | 1.02 |
| Ashraf Elnagar | 5 | 0 | 1.01 |