id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_gbi3ah5ymfdatpixrkkboizbqy	Longzhi Yang	Job shop planning and scheduling for manufacturers with manual operations	2018	26	.pdf	application/pdf	12756	1266	73	This paper proposes a complete manual job scheduling solution to address these limitations using a genetic algorithm (GA) and an adaptive fuzzy inference system by further developing the seminal work reported in Yang et In particular, these inference systems are able to represent non-linear and high dimensional decision making problems as fuzzy rule bases. The experience-based fuzzy rule interpolation is particularly useful in this work for manual task completion time The completion time of a manual task is estimated by the experience-based fuzzy interpolation system as introduced is used in this work to initialise a fuzzy rule base for the estimation of the completion times of collate and pack tasks to optimise the lane planning and job scheduling, by minimising the time cost of the collate and pack operations and completion time required for the given task on a lane with 1 worker (i.e., z1 = 9.37) can be interpolated from neighbouring rules R1	./cache/work_gbi3ah5ymfdatpixrkkboizbqy.pdf	./txt/work_gbi3ah5ymfdatpixrkkboizbqy.txt