Research on the surface machining plan of hull shell based on PSO optimized NSGA-II algorithm

Author(s):  
Yue Huang ◽  
Liang Qi ◽  
Shuxia Ye ◽  
Chengwei Ge
Keyword(s):  
Nsga Ii ◽  
2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.


2020 ◽  
Vol 8 (4) ◽  
pp. 276-286
Author(s):  
Vu Duc Quyen ◽  
Andrey Ronzhin

Three posterior algorithms NSGA-II, MOGWO and MOPSO to solve the problem of multicriteria optimization of the robotic gripper design are considered. The description of the kinematic model of the developed prototype of the four-fingered gripper for picking tomatoes, its limitations and objective functions used in the optimization of the design are given. The main advantage of the developed prototype is the use of one actuator for the control of the fingers and the suction nozzle. The results of optimization of the kinematic model and the dimensions of the elements of robotic gripper using the considered posterior algorithms are presented.


Author(s):  
Apangshu Das ◽  
Sambhu Nath Pradhan

Background: Output polarity of the sub-function is generally considered to reduce the area and power of a circuit at the two-level realization. Along with area and power, the power-density is also one of the significant parameter which needs to be consider, because power-density directly converges to circuit temperature. More than 50% of the modern day integrated circuits are damaged due to excessive overheating. Methods: This work demonstrates the impact of efficient power density based logic synthesis (in the form of suitable polarity selection of sub-function of Programmable Logic Arrays (PLAs) for its multilevel realization) for the reduction of temperature. Two-level PLA optimization using output polarity selection is considered first and compared with other existing techniques and then And-Invert Graphs (AIG) based multi-level realization has been considered to overcome the redundant solution generated in two-level synthesis. AIG nodes and associated power dissipation can be reduced by rewriting, refactoring and balancing technique. Reduction of nodes leads to the reduction of the area but on the contrary increases power and power density of the circuit. A meta-heuristic search approach i.e., Nondominated Sorting Genetic Algorithm-II (NSGA-II) is proposed to select the suitable output polarity of PLA sub-functions for its optimal realization. Results: Best power density based solution saves up to 8.29% power density compared to ‘espresso – dopo’ based solutions. Around 9.57% saving in area and 9.67% saving in power (switching activity) are obtained with respect to ‘espresso’ based solution using NSGA-II. Conclusion: Suitable output polarity realized circuit is converted into multi-level AIG structure and synthesized to overcome the redundant solution at the two-level circuit. It is observed that with the increase in power density, the temperature of a particular circuit is also increases.


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