2021
DOI: 10.1007/s10462-021-10042-y
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A survey on evolutionary computation for complex continuous optimization

Abstract: Complex continuous optimization problems widely exist nowadays due to the fast development of the economy and society. Moreover, the technologies like Internet of things, cloud computing, and big data also make optimization problems with more challenges including Many-dimensions, Many-changes, Many-optima, Many-constraints, and Many-costs. We term these as 5-M challenges that exist in large-scale optimization problems, dynamic optimization problems, multi-modal optimization problems, multi-objective optimizati… Show more

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Cited by 214 publications
(67 citation statements)
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References 310 publications
(315 reference statements)
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“…An increase in the enrichment content of O2 tends to increase the temperature of the blast furnace and decrease the amount of nitrogen injected, thereby increasing the thermal level and favoring the permeability of the blast furnace. Thus, a high or thicker cohesive zone tends to increase the silicon content in the hot metal as well as a higher thermal level which favors the conditions for the incorporation of silicon into the hot metal, which may indeed be influenced by variables [49]- [51].…”
Section: Resultsmentioning
confidence: 99%
“…An increase in the enrichment content of O2 tends to increase the temperature of the blast furnace and decrease the amount of nitrogen injected, thereby increasing the thermal level and favoring the permeability of the blast furnace. Thus, a high or thicker cohesive zone tends to increase the silicon content in the hot metal as well as a higher thermal level which favors the conditions for the incorporation of silicon into the hot metal, which may indeed be influenced by variables [49]- [51].…”
Section: Resultsmentioning
confidence: 99%
“…In the future, we will focus on other types of JSSPs (e.g., flexible JSSPs [49], [50], flow shop scheduling problems [51]- [53]), and extend the MPMO framework with other evolutionary computation [54] (e.g., particle swarm optimization [55]- [57], differential evolution [58]- [60], estimation of distribution algorithm [61], and gravitational search algorithm [62]) for efficiently solving them. Besides, the incorporation with distributed computing technique [63]- [65] or matrix-based technique [66] will be further studied to reduce the running time of the algorithm.…”
Section: Discussionmentioning
confidence: 99%
“…For future work, the proposed algorithm will be further extended to solving more difficult and complex MTOPs, such as not only in complex continuous space [54]- [56], but also in complex discrete [57]- [60], combinational [61]- [64], and mix-variable space [65]- [67]. Furthermore, as the MKT is a generic idea, further exploration of other kinds of meta-knowledge and other meta-knowledge transfer methods and utilization methods are worthy studied to obtain more powerful EMTO algorithms.…”
Section: Discussionmentioning
confidence: 99%