A comprehensive review on human–robot collaboration remanufacturing towards uncertain and dynamic disassembly

Open Access

Review

Table 4

The comparisons between various disassembly optimization methods and disassembly characteristics by reviewing the related literatures.

Disassembly optimization methods	References.	Disassembly sequence optimization	Disassembly line balance	Scenario recognition and object tracking
Genetic Algorithms	Go et al. [88]	√	√
	Kheder et al. [89]	√
	Tseng et al. [90]		√
Ant Colony	Lu et al. [91]	√	√
	McGovern et al. [92]	√
	Hu et al. [93]	√	√
Artificial bee colony	Liu et al. [94]	√	√
	Hartono et al. [95]		√
	Kalayci et al. [96]	√
	Zhang et al. [97]	√	√
Particle swarm optimization	Pornsing et al. [98]	√	√
	Tseng et al. [99]	√
	Tao et al. [100]	√	√
	Kalayci et al. [101]		√
Tabu search	Alshibli et al. [102]	√	√
	Tao et al. [103]		√
	Kalayci et al. [104]	√	√
	Liang et al. [105]		√
Simulated annealing	Xia et al. [106]		√
	Fang et al. [107]		√
	Wang et al. [108]		√
Reinforcement learning	Chu et al. [109]	√
Reinforcement learning	Allagui et al. [110]	√
Convolutional neural networks	Yildiz et al. [111]			√
	Li et al. [112]			√
	Adesso et al. [113]			√
YOLO algorithms	Brogan et al. [114]			√
	Mangold et al. [115]			√
	Zhang et al. [116]			√
Recurrent neural network	Zhang et al. [117]			√
Long short-term memory	Deng et al. [118]			√
Long short-term memory	Chen et al. [119]			√

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