A hybrid optimization approach for sustainable process planning and scheduling

被引：40
|
作者：
Li, X. X. [1 ,2 ]
Li, W. D. [2 ]
Cai, X. T. [3 ]
He, F. Z. [3 ]
机构：
[1] Huazhong Agr Univ, Coll Informat, Wuhan, Hubei, Peoples R China
[2] Coventry Univ, Fac Engn & Comp, Coventry CV1 5FB, W Midlands, England
[3] Wuhan Univ, Sch Comp Sci & Technol, Wuhan 430072, Hubei, Peoples R China
来源：
INTEGRATED COMPUTER-AIDED ENGINEERING | 2015年 / 22卷 / 04期
关键词：
Honey bee mating optimization; simulated annealing; sustainable manufacturing; process planning; scheduling; PARTICLE SWARM OPTIMIZATION; ENERGY-REQUIREMENTS; MATING OPTIMIZATION; GENETIC ALGORITHM; MODELS; BEES; TRANSPORTATION; CONSUMPTION; SYSTEMS; DESIGN;
D O I：
10.3233/ICA-150492
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Process planning and scheduling are important stages in manufacturing, and good strategies can significantly improve the energy performance of manufacturing to achieve sustainability. In this paper, an innovative optimization approach has been developed to facilitate sustainable process planning and scheduling. In the approach, honey-bee mating and annealing processes are simulated to optimize multi-objectives including energy consumption, makespan and the balanced machine utilization. Experiments on practical cases show that the optimization results from this approach are promising in comparison with those from a genetic algorithm, a honey bee mating optimization algorithm, ant colony optimization and a simulated annealing algorithm, respectively.
引用
收藏
页码：311 / 326
页数：16
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