首页|New Findings from Beijing University of Technology in the Area of Robotics Repor ted (Robotic Assembly Line Balancing Considering the Carbon Footprint Objective With Cross-station Design)
New Findings from Beijing University of Technology in the Area of Robotics Repor ted (Robotic Assembly Line Balancing Considering the Carbon Footprint Objective With Cross-station Design)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting originating from Beijing, People's R epublic of China, by NewsRx correspondents, research stated, "Robotic assembly l ines are widely applied in the manufacturing sector to produce a wide range of p roducts because of their efficiency and multifunctionality. The robotic assembly line balancing problem (RALBP) is a combinatorial optimization problem where th e decision variables are task assignment and robot allocation." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Ministry of Education, China. Our news editors obtained a quote from the research from the Beijing University of Technology, "However, RALBP considering carbon footprint, which is a very sig nificant environmental concern, has scarcely been studied in the literature and a practical ‘cross-station'design is never mathematically formulated. In this pa per, a mixed -integer programming model is proposed to optimize the two objectiv es according to the Pareto principle. A particle swarm algorithm (PSO) with some improvement rules is designed to solve the problem. To examine the efficiency o f the algorithm, computational experiments including five medium-sized and five large -sized datasets are conducted. The results show that the efficiency of PSO is better than that of four other classic algorithms in terms of three evaluati on metrics."
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningRoboticsRobotsBeijing University of Technology
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