The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition （CI） engine using jatropha biodiesel. Response su...The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition （CI） engine using jatropha biodiesel. Response surface methodology based on Central composite design （CCD） is used to design the experiments. Mathematical models are developed for combustion parameters （Brake specific fuel consumption （BSFC） and peak cylinder pressure （Pmax））, performance parameter brake thermal efficiency （BTE） and emission parameters （CO, NOx, unburnt HC and smoke） using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion （BSFC, Pmax）, performance （BTE） and emission （CO, NOx, HC, smoke） parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NOx, HC, smoke, a multi- objective optimization problem is formulated. Non- dominated sorting genetic algorithm-II is used in predict- ing the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine outputand emission parameters depending upon their own requirements.展开更多
采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对通信电缆的绞合节距进行优化,以通信电缆的导体用量和近端串音衰减为优化目标,获得一组多样化的Pareto解集,为绞合节距的设计提供了优选空间.以25线对通信电缆的绞合节距为优化对象,结果...采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对通信电缆的绞合节距进行优化,以通信电缆的导体用量和近端串音衰减为优化目标,获得一组多样化的Pareto解集,为绞合节距的设计提供了优选空间.以25线对通信电缆的绞合节距为优化对象,结果表明,经优化获得157个Pareto解,其目标函数导体用量位于区间[55.93 kg/km,56.74 kg/km],近端串音衰减位于区间[58.11 d B/km,94.77 d B/km];与粒子群算法(PSO)相比,在收敛时长相似的情况下,NSGA-Ⅱ的优化结果支配度100%优于PSO,其解集分布均匀程度也显著优于PSO.展开更多
Tolerance charting is an effective tool to determine the optimal allocation of working dimensions and working tolerances such that the blueprint dimensions and tolerances can be achieved to accomplish the cost objecti...Tolerance charting is an effective tool to determine the optimal allocation of working dimensions and working tolerances such that the blueprint dimensions and tolerances can be achieved to accomplish the cost objectives.The selection of machining datum and allocation of tolerances are critical in any machining process planning as they directly affect any setup methods/machine tools selection and machining time.This paper mainly focuses on the selection of optimum machining datums and machining tolerances simultaneously in process planning.A dynamic tolerance charting constraint scheme is developed and implemented in the optimization procedure.An optimization model is formulated for selecting machining datum and tolerances and implemented with an algorithm namely Elitist Non-Dominated Sorting Genetic Algorithm（NSGA-II）.The computational results indicate that the proposed methodology is capable and robust in finding the optimal machining datum set and tolerances.展开更多
This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation...This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.展开更多
文摘The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition （CI） engine using jatropha biodiesel. Response surface methodology based on Central composite design （CCD） is used to design the experiments. Mathematical models are developed for combustion parameters （Brake specific fuel consumption （BSFC） and peak cylinder pressure （Pmax））, performance parameter brake thermal efficiency （BTE） and emission parameters （CO, NOx, unburnt HC and smoke） using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion （BSFC, Pmax）, performance （BTE） and emission （CO, NOx, HC, smoke） parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NOx, HC, smoke, a multi- objective optimization problem is formulated. Non- dominated sorting genetic algorithm-II is used in predict- ing the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine outputand emission parameters depending upon their own requirements.
文摘采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对通信电缆的绞合节距进行优化,以通信电缆的导体用量和近端串音衰减为优化目标,获得一组多样化的Pareto解集,为绞合节距的设计提供了优选空间.以25线对通信电缆的绞合节距为优化对象,结果表明,经优化获得157个Pareto解,其目标函数导体用量位于区间[55.93 kg/km,56.74 kg/km],近端串音衰减位于区间[58.11 d B/km,94.77 d B/km];与粒子群算法(PSO)相比,在收敛时长相似的情况下,NSGA-Ⅱ的优化结果支配度100%优于PSO,其解集分布均匀程度也显著优于PSO.
文摘Tolerance charting is an effective tool to determine the optimal allocation of working dimensions and working tolerances such that the blueprint dimensions and tolerances can be achieved to accomplish the cost objectives.The selection of machining datum and allocation of tolerances are critical in any machining process planning as they directly affect any setup methods/machine tools selection and machining time.This paper mainly focuses on the selection of optimum machining datums and machining tolerances simultaneously in process planning.A dynamic tolerance charting constraint scheme is developed and implemented in the optimization procedure.An optimization model is formulated for selecting machining datum and tolerances and implemented with an algorithm namely Elitist Non-Dominated Sorting Genetic Algorithm（NSGA-II）.The computational results indicate that the proposed methodology is capable and robust in finding the optimal machining datum set and tolerances.
文摘This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.
