Sustainability on farms is a challenge to competitiveness in the globalized market. In this scenario, due to the strong environmental, economic and social appeal, crop-livestock-forest integration systems have been co...Sustainability on farms is a challenge to competitiveness in the globalized market. In this scenario, due to the strong environmental, economic and social appeal, crop-livestock-forest integration systems have been considered as the future of agriculture. Regarding the economic approach, this system is based on the diversification of income generating activities, with revenue entry at different times, rationalization of resource use and reduction of risk of financial losses. Thus, the purpose of this work was to carry out the economic analysis of a crop-livestock-forest integration system, located at Boa Vereda＇s farm, in the municipality of Cachoeira Dourada in the state of Goi^is in the central-west region of Brazil. The system was composed of the following traditional crops of the region： soybean, corn, pasture, beef cattle and eucalyptus. The technical coefficients and the prices used for economic evaluation were obtained from the experimental unit and from the local market when crops were harvested in 2016/2017. The economic indicators used to assess economic viability were the net present value （NPV） and the equivalent annual uniform value （EAUV）. The results showed a return greater than the opportunity cost of the land, showing the attractiveness of the crop-livestock-forest integration system. Thus, this system represents an economically viable alternative that, among other benefits, allows the diversification of its sources of income, with a reduction of risk.展开更多
Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and th...Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and the machining parameters of machine, tool and tool access direction （TAD） for each operation. This paper proposes a novel optimization strategy for process planning that considers different dimensions of the problem in parallel. A multi-dimensional tabu search （MDTS） algo-rithm based on this strategy is developed to optimize the four dimensions of a process plan, namely, operation sequence （OperSeq）, machine sequence （MacSeq）, tool sequence （TooISeq） and tool approach direction sequence （TADSeq）, sequentially and iteratively. In order to improve its efficiency and stability, tabu search, which is incorporated into the proposed MDTS al- gorithm, is used to optimize each component of a process plan, and some neighbourhood strategies for different components are presented for this tabu search algorithm. The proposed MDTS algorithm is employed to test four parts with different numbers of operations taken from the literature and compared with the existing algorithms like genetic algorithm （GA）, simulated annealing （SA）, tabu search （TS） and particle swarm optimization （PSO）. Experimental results show that the developed algo-rithm outperforms these algorithms in terms of solution quality and efficiency.展开更多
文摘Sustainability on farms is a challenge to competitiveness in the globalized market. In this scenario, due to the strong environmental, economic and social appeal, crop-livestock-forest integration systems have been considered as the future of agriculture. Regarding the economic approach, this system is based on the diversification of income generating activities, with revenue entry at different times, rationalization of resource use and reduction of risk of financial losses. Thus, the purpose of this work was to carry out the economic analysis of a crop-livestock-forest integration system, located at Boa Vereda＇s farm, in the municipality of Cachoeira Dourada in the state of Goi^is in the central-west region of Brazil. The system was composed of the following traditional crops of the region： soybean, corn, pasture, beef cattle and eucalyptus. The technical coefficients and the prices used for economic evaluation were obtained from the experimental unit and from the local market when crops were harvested in 2016/2017. The economic indicators used to assess economic viability were the net present value （NPV） and the equivalent annual uniform value （EAUV）. The results showed a return greater than the opportunity cost of the land, showing the attractiveness of the crop-livestock-forest integration system. Thus, this system represents an economically viable alternative that, among other benefits, allows the diversification of its sources of income, with a reduction of risk.
基金supported by the State Key Program of National Natural Science Foundation of China (Grant No. 51035001)National Natural Science Foundation of China (Grant Nos. 50825503, 50875101)
文摘Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and the machining parameters of machine, tool and tool access direction （TAD） for each operation. This paper proposes a novel optimization strategy for process planning that considers different dimensions of the problem in parallel. A multi-dimensional tabu search （MDTS） algo-rithm based on this strategy is developed to optimize the four dimensions of a process plan, namely, operation sequence （OperSeq）, machine sequence （MacSeq）, tool sequence （TooISeq） and tool approach direction sequence （TADSeq）, sequentially and iteratively. In order to improve its efficiency and stability, tabu search, which is incorporated into the proposed MDTS al- gorithm, is used to optimize each component of a process plan, and some neighbourhood strategies for different components are presented for this tabu search algorithm. The proposed MDTS algorithm is employed to test four parts with different numbers of operations taken from the literature and compared with the existing algorithms like genetic algorithm （GA）, simulated annealing （SA）, tabu search （TS） and particle swarm optimization （PSO）. Experimental results show that the developed algo-rithm outperforms these algorithms in terms of solution quality and efficiency.
