Table 7.

Bio-inspired multi-objective optimization algorithms and selected examples of their applications in microelectronics and photonics including sensorics and fog/cloud computing.

Algorithm Name	Some Applications, References
Multi-Objective (MO) Genetic Algorithm	Improvement of photoelectric performance of thin film solar cells [184] Optimization of nanosecond laser processing [185] VLSI floor planning optimization regarding measures such as area, wire length and dead space between modules [186] Lifetime reliability, performance and power consumption of heterogeneous multiprocessor embedded systems [187]
MO Particle Swarm Optimization	Review of many applications of MO PSO in diverse areas [188] Floor planning of the VLSI circuit and layout area minimization using MO PSO [189]
MO Ant Colony Optimization	A 3D printed bandpass frequency-selective surface structure with desired center frequency and bandwidth [190] Analog filter design [191] Multi-criteria optimization for VLSI floor planning [192]
Artificial Bee Colony	Area and power optimization for logic circuit design [193] Design of digital filters [194]
Artificial Immune System	Spectrum management and design of 6G networks [195] Multi-objective design of an inductor for a DC-DC buck converter [196]
Differential Evolution	Geometry optimization of high-index dielectric nanostructures [197] Multi-objective synchronous modeling and optimal solving of an analog IC [198]
Firefly Algorithm	Reducing heat generation, sizing and interconnect length for VLSI floor planning [199] Secure routing for fog-based wireless sensor networks [200]
Cuckoo Search	Multi-objective-derived energy-efficient routing in wireless sensor networks [201] Parameter extraction of photovoltaic cell based on a multi-objective approach [202]
MO Grey Wolf Optimizer	Electrochemical micro-drilling in MEMS [203] Multi-objective task scheduling in cloud-fog computing [204]