Optimisation Design of Six-Bar Double Dwell Mechanisms: A New Approach

2011 ◽  
Vol 110-116 ◽  
pp. 5216-5222 ◽  
Author(s):  
Mohan Jagannath
Keyword(s):  
Genetic Algorithm ◽  
Synthesis Problem ◽  
Simple Manner ◽  
Nsga Ii ◽  
Recent Contribution ◽  
New Approach ◽  
Constrained Optimisation ◽  
Function Generation ◽  
Concept Of Function ◽  
Single Objective

This paper introduces a new approach for me-chanical design of planar six-bar linkages with rotary joints which produce two dwells in each cycle of the input crank. The approach builds on the concept of function generation in a simple manner. The synthesis problem is posed as a single-objective constrained optimisation problem. A genetic algorithm-based optimisation scheme, namely the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) has been used for solving the optimisation problem. The proposed method has been illustrated by means of an example problem from a recent contribution to literature. It is seen that the results compare favourably with the existing work.

scholarly journals Distributed Query Plan Generation Using Multiobjective Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Shina Panicker ◽  
T. V. Vijay Kumar
Keyword(s):  
Genetic Algorithm ◽  
Query Processing ◽  
Experimental Comparison ◽  
Nsga Ii ◽  
Query Plan ◽  
Multiobjective Genetic Algorithm ◽  
Plan Generation ◽  
Distributed Query ◽  
Processing Cost ◽  
Single Objective

A distributed query processing strategy, which is a key performance determinant in accessing distributed databases, aims to minimize the total query processing cost. One way to achieve this is by generating efficient distributed query plans that involve fewer sites for processing a query. In the case of distributed relational databases, the number of possible query plans increases exponentially with respect to the number of relations accessed by the query and the number of sites where these relations reside. Consequently, computing optimal distributed query plans becomes a complex problem. This distributed query plan generation (DQPG) problem has already been addressed using single objective genetic algorithm, where the objective is to minimize the total query processing cost comprising the local processing cost (LPC) and the site-to-site communication cost (CC). In this paper, this DQPG problem is formulated and solved as a biobjective optimization problem with the two objectives being minimize total LPC and minimize total CC. These objectives are simultaneously optimized using a multiobjective genetic algorithm NSGA-II. Experimental comparison of the proposed NSGA-II based DQPG algorithm with the single objective genetic algorithm shows that the former performs comparatively better and converges quickly towards optimal solutions for an observed crossover and mutation probability.

The Dudley Lee Case: A new approach to factual causation and its implications for transformative jurisprudence

2017 ◽  
Vol 30 (1) ◽  
pp. 273-289
Author(s):  
Anmari Meerkotter
Keyword(s):  
Case Note ◽  
Constitutional Court ◽  
Recent Contribution ◽  
New Approach ◽  
State Accountability ◽  
The Law ◽  
Transformative Impact ◽  
Constitutional Jurisprudence ◽  
Law Of Delict

The Constitutional Court (CC) judgment of Lee v Minister of Correction Services 2013 2SA 144 (CC) is a recent contribution to transformative constitutional jurisprudence in the field of the law of delict. This matter turned on the issue of factual causation in the context of wrongful and negligent systemic omissions by the state. In this case note, I explore the law relating to this element of delictual liability with specific regard to the traditional test for factual causation – the conditio sine qua non (‘but-for’) test. In particular, I note the problems occasioned by formalistic adherence to this test in the context of systemic state omissions as evidenced by the SCA judgment in the same matter. I also consider the manner in which English courts have addressed this problem. Thereafter, I analyse the CC’s broader approach to the determination of factual causation as one based on common sense and justice. I argue that this approach endorses a break from a formalistic application of the test and constitutes a step towards an approach which resonates with the foundational constitutional values of freedom, dignity and equality. Furthermore, it presents an appropriate solution to the problems associated with factual causation where systemic omissions are concerned. I then consider the transformative impact of the Lee judgment. In particular, I argue that the broader enquiry favoured by the CC facilitates the realisation of constitutionally guaranteed state accountability, and amounts to an extension of the existing norm of accountability jurisprudence. Hence, I contend that the judgment presents a further effort by the Constitutional Court to effect wholesale the constitutionalisation of the law of delict, as well as a vindicatory tool to be used by litigants who have been adversely affected by systemic state omissions.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

scholarly journals Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 11 (9) ◽  
pp. 2571
Author(s):  
Xujing Zhang ◽  
Lichuan Wang ◽  
Yan Chen
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Optimal Solution ◽  
Material Distribution ◽  
Low Carbon ◽  
Nsga Ii ◽  
Management Objectives ◽  
Multi Objective Genetic Algorithm ◽  
Distribution Process ◽  
The Cost

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

Shape optimization of egg-shaped sewer pipes based on the nondominated sorting genetic algorithm (NSGA-II)

2022 ◽  
Vol 204 ◽  
pp. 111999
Author(s):  
Hanting Wu ◽  
Yangrui Huang ◽  
Lei Chen ◽  
Yingjie Zhu ◽  
Huaizheng Li
Keyword(s):  
Genetic Algorithm ◽  
Shape Optimization ◽  
Nsga Ii ◽  
Sewer Pipes ◽  
Nondominated Sorting
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