A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem

doi:10.16183/j.cnki.jsjtu.2019.321

Abstract

Abstract:

Aimed at the no-idle flow-shop scheduling problem (NIFSP) with minimized makespan, a discrete sine optimization algorithm (DSOA) is proposed. Inspired by sine waveforms, the original sine optimization algorithm (SOA) is a global optimization algorithm, which uses the sine function to update the position of search agents. First, the update position strategy to adapt to the combinatorial optimization problem is redefined. An iterated greedy algorithm with a variable removing size is employed to update the position to enhance the exploration ability. Then, a crossover strategy and a selection strategy are applied to avoid the algorithm falling into local optimum. Next, to improve the exploitation ability of local search and the accuracy of the algorithm, an insertion-based local search scheme is applied in DSOA to search for a better solution around the current optimal solution. Finally, based on the Taillard benchmark, the simulation results of performance comparisons are presented. The experimental results demonstrate the effectiveness of the proposed DSOA algorithm for solving NIFSP.

Key words: production scheduling, sine optimization algorithm, no-idle flow-shop scheduling problem (NIFSP), iterated greedy algorithm, makespan, intelligent optimization algorithm, local search

CLC Number:

TP278

ZHAO Rui, GU Xingsheng. A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem[J]. Journal of Shanghai Jiao Tong University, 2020, 54(12): 1291-1299.

Figures/Tables 9

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算例	α=0.1			α=0.3			α=0.5
算例	avg	min	ARPD	avg	min	ARPD	avg	min	ARPD
Ta051	5442.1	5398	1.14	5401.6	5381^*	0.38	5399.3	5386	0.34
Ta061	5834.1	5833^*	0.02	5833.0	5833^*	0.00	5833.0	5833^*	0.00
Ta071	6751.5	6736	0.35	6742.8	6728^*	0.22	6740.1	6728^*	0.18
Ta081	9337.6	9327	0.21	9327.8	9318^*	0.11	9324.2	9319	0.07

算例	规模		SOA	DSOA¹		DSOA²		DSOA³		DSOA
算例	n	m	C_max	C_max	PIP	C_max	PIP	C_max	PIP	C_max	PIP
Ta001	20	5	1 439.2	1 384.5	3.801%	1 383.5	3.870%	1 381.4	4.016%	1 380.6	4.072%
Ta011	20	10	2 331.0	2 198.7	5.676%	2 196.6	5.766%	2 198.6	5.680%	2 196.4	5.774%
Ta021	20	20	3 621.5	3 222.9	11.006%	3 215.0	11.225%	3213.1	11.277%	3 212.2	11.302%
Ta031	50	5	3 082.6	3 014.0	2.225%	3 014.0	2.225%	3 014.0	2.225%	3 014.0	2.225%
Ta041	50	10	3 935.8	3 435.7	12.706%	3 438.1	12.645%	3427.2	12.922%	3 423.0	13.029%
Ta051	50	20	6 383.3	5 430.2	14.931%	5 450.0	14.621%	5 411.1	15.230%	5 399.3	15.415%
Ta061	100	5	6 092.9	5 833.4	4.259%	5 833.1	4.264%	5 833.0	4.266%	5 833.0	4.266%
Ta071	100	10	7 403.3	6 756.7	8.734%	6 764.6	8.627%	6 750.0	8.824%	6 740.1	8.958%
Ta081	100	20	10 735.4	9 355.5	12.854%	9 353.2	12.875%	9 327.7	13.113%	9 324.2	13.145%
Ta091	200	10	12 826.8	11 683.4	8.914%	11 691.2	8.853%	11 651.6	9.162%	11 645.4	9.210%
Ta101	200	20	17 351.8	14 918.5	14.023%	14 982.0	13.657%	14 857.5	14.375%	14 841.8	14.465%
均值					9.012%		8.966%		9.190%		9.260%

规模		DSOA		DFWA-LS		IWO
n	m	ARPD	SD	ARPD	SD	ARPD	SD
20	5	0.05	0.008	0.15	0.013	0.92	0.083
	10	0.21	0.034	0.62	0.060	2.37	0.156
	20	0.21	0.057	0.51	0.093	2.33	0.272
50	5	0.00	0.000	0.01	0.004	0.49	0.103
	10	0.29	0.048	0.52	0.085	2.76	0.311
	20	0.37	0.113	0.64	0.174	4.04	0.497
100	5	0.00	0.002	0.03	0.011	0.61	0.141
	10	0.05	0.016	0.13	0.056	1.39	0.361
	20	0.22	0.091	0.35	0.154	3.66	0.651
200	10	0.05	0.041	0.13	0.098	1.85	0.397
	20	0.20	0.146	0.27	0.244	3.93	0.891
均值		0.15	0.050	0.31	0.090	2.21	0.351