A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

Table 3

Comparison of the results.

Reference	CA	NBPS	NBKSO		ARD (%)		Improvement in the proposed HGA
			CA	Proposed HGA	CA	Proposed HGA	(%)
Rakkiannan and Palanisamy [16]	HGAPSA	11	2	6	0.7	0.7	0
Asadzadeh and Zamanifar [33]	PGA	34	14	26	3.4	0.2	3.2
Luh and Chueh [40]	MMIA	18	16	17	0.32	0.02	0.3
Yang et al. [41]	MA	22	20	20	0.04	0.03	0.01
Hasan et al. [42]	HGA	14	11	14	0.49	0.00	0.49
Lin and Yugeng [31]	HGA	42	26	29	0.65	0.35	0.3
Gonçalves et al. [30]	Param	42	30	29	0.41	0.35	0.06
Ombuki and Ventresca [29]	LSGA	27	3	14	5.41	0.54	4.87
	HGA	27	6	14	4.07	0.54	3.53
Coello et al. [19]	AIS	23	12	14	1.61	0.44	1.17
Binato et al. [43]	Grasp	42	23	29	1.8	0.35	1.45
Wang and Zheng [27]	HGA	9	7	6	0.38	0.28	0.1
Sabuncuoglu and Bayiz [44]	BS	40	16	27	4.23	0.36	3.87
Nuijten and Aarts [45]	RCS	42	30	29	0.63	0.35	0.28

NBPS: number of benchmarked problems solved.
NBKSO: number of best known solutions obtained.
ARD: average relative deviation in percentage.
CA: compared algorithms.