Energy-Saving Scheduling in a Flexible Flow Shop Using a Hybrid Genetic Algorithm  

作　　者：Rong-Hwa Huang Shun-Chi Yu Po-Han Chen 

机构地区：[1]Department of Business Administration, Fu Jen Catholic University, Taiwan [2]Department of Tourism and Hospitality, China University of Science and Technology, Taiwan

出　　处：《Journal of Environmental Protection》2017年第10期1037-1056,共20页环境保护（英文）

摘　　要：Many researches discussing reduced energy consumption for environmental protection focus on machine efficiency or process redesign. To optimize the machine operation time can also save the energy, and these researches have received great interests in recent years. This study considers three different states of machines, among processing there are two different speeds, to solve the problem of minimizing energy costs under time-of-use tariff with no tardy jobs in flexible flow shop. This problem is basically NP-hard, we proposed a hybrid genetic algorithm (GA) to solve problems in reasonable timeliness. The result shows that to optimize different states of machines under time-of use tariff can reduce energy costs significantly in on-time delivery.Many researches discussing reduced energy consumption for environmental protection focus on machine efficiency or process redesign. To optimize the machine operation time can also save the energy, and these researches have received great interests in recent years. This study considers three different states of machines, among processing there are two different speeds, to solve the problem of minimizing energy costs under time-of-use tariff with no tardy jobs in flexible flow shop. This problem is basically NP-hard, we proposed a hybrid genetic algorithm (GA) to solve problems in reasonable timeliness. The result shows that to optimize different states of machines under time-of use tariff can reduce energy costs significantly in on-time delivery.

关 键 词：FLEXIBLE Flow SHOPS ENERGY-SAVING GENETIC Algorithm Energy CONSUMPTION Cost Non-Tardy GENETIC Algorithms 

分 类 号：R73[医药卫生—肿瘤]