Table 3 Metaheuristic applications on different domains
Related Figures (31)
Table 1 Keywords and search results on the selected venues these algorithms create a trajectory in the search space. Here, it is noteworthy that the solution may or may not belong to neighborhood of the current solution. For a population-based algorithm, a population of multiple solutions is generated initially. Then, in every iteration, a set of solutions are manipulated in order to find solutions toward better search areas. These algorithms either do recombinations of multiple solutions or modify each via the strategy adopted to enforce exploration and exploitation of the search area (Blum and Roli 2003). Now that the above discussion has already established preliminary knowledge about meta- je ES ns ne Se, mE ee, es ON oe i a ea ee en, or Table 2 Survey results Fig. 3. Publication venues with type of metaheuristic publications The primary data collected in this study revealed around 140 metaheuristics (listed in ‘Appendix A”) applied in diversified range of fields broadly in the area of science and tech- 10logy, economics, and daily life. Fig. 4 infers that mostly metaheuristics have been applied and tested on numerical problems which include continuous and discrete, constrained and inconstrained, single and multi-objective optimization problems, etc. Data mining is another ield of interest mostly chosen by metaheuristic researchers, which includes optimization asks involved in classification, prediction, clustering, and system modeling, etc. Among top oractical applications, metaheursitics have been utilized to find optimum solutions for power eneration and distribution, and electronics board designing in the field of electrical and elec- ronics. Many industrial applications require scheduling jobs to be assigned on sequential yr parallel processes in order to optimized cost. Another promising area of metaheuristic ipplications is combinatorial optimization problems ranging from facility location problems O set-covering, to more difficult multi-agent task allocation in extreme teams, etc. Other ipplications among top ten areas include communications (networking, telecommunication, antennas and radar design, etc.), transportation (traveling salesman problem, routing, shortest oath, etc.), engineering (mechanical designs, aircraft and ship components design, etc.), civil sngineering (structural design, buildings and bridges, construction, etc.), and information and communications technology—ICT (cloud and grid computing, swarm robotics, security, software development, etc.). The applications of metaheuristics need to be explored in the ireas of mining, traffic control, manufacturing and production, etc. Table 3 continued Table 3 continued Table 3 continued Table 3 continued Table 3 continued Table 3 continued Fig. 5 Number of publications of metaheuristics Fig. 6 Metaphor disciplines adopted by researchers for designing metaheuristics Fig. 7 Metaphors adopted by researchers for designing new metaheuristics See Table 4. Table 4 continued Table 4 continued Stochastic Diffusion Search (al Rifaie et al. 2011)
