Optimal Configuration of a Genetic Algorithm for Command Space Layout Analysis

2018 ◽  
Vol 62 (1) ◽  
pp. 383-387 ◽  
Author(s):  
Wenbi Wang
Keyword(s):  
Genetic Algorithm ◽  
Population Size ◽  
Simulation Experiment ◽  
Large Population ◽  
Spatial Layout ◽  
Search Efficiency ◽  
Medium Level ◽  
Military Command ◽  
Space Layout ◽  
The Impact

A genetic algorithm was developed to optimize the spatial layout of military command centres. This paper describes a simulation experiment in which the impact of key algorithm parameters on its search efficiency was examined. The results confirmed the benefit of a large population size and a long evolution process for improving the search effectiveness. For the parameter that controls the rate of introducing new solutions (i.e., probability of swap), a medium level configuration was found to be superior. Results of this study provide guidelines and heuristics for configuring key parameters of the proposed algorithm so that its search efficiency and computational expense are best balanced.

GALO: A Tool for Command Space Layout Optimization Using a Genetic Algorithm

2019 ◽  
Vol 63 (1) ◽  
pp. 521-525 ◽  
Author(s):  
Wenbi Wang ◽  
Jonathan Lin
Keyword(s):  
Genetic Algorithm ◽  
Simulation Experiment ◽  
Layout Design ◽  
Optimal Solutions ◽  
Algorithmic Approach ◽  
Software Program ◽  
Military Command ◽  
Analytical Assessment ◽  
Mission Control ◽  
Space Layout

This paper describes a software program that was developed to assist the layout design of collaborative workplaces such as a military command centre. The program assesses layout quality based on its support to operator collaboration and searches for optimal solutions using a genetic algorithm. A simulation experiment was conducted to examine the program’s effectiveness. The study involved the allocation of a 10-person team to a command centre that was pre-configured with a mission control style layout. Across 50 simulation runs, a total of 38 unique optimal layouts were identified. These solutions shared an equivalent quality as measured by the objective metric used by the algorithm. Analytical assessment confirmed their optimality for this design problem. The software program provides a useful tool for human factors practitioners to examine layout options of complex workplaces based on an algorithmic approach.

scholarly journals Choosing Mutation and Crossover Ratios for Genetic Algorithms—A Review with a New Dynamic Approach

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 390 ◽  
Author(s):  
Ahmad Hassanat ◽  
Khalid Almohammadi ◽  
Esra’a Alkafaween ◽  
Eman Abunawas ◽  
Awni Hammouri ◽  
...  
Keyword(s):  
Population Size ◽  
Optimization Problems ◽  
Large Population ◽  
Small Population ◽  
Mutation Rates ◽  
Mutation Operators ◽  
Tuning Methods ◽  
Two Parameters ◽  
The Impact ◽  
Crossover And Mutation

Genetic algorithm (GA) is an artificial intelligence search method that uses the process of evolution and natural selection theory and is under the umbrella of evolutionary computing algorithm. It is an efficient tool for solving optimization problems. Integration among (GA) parameters is vital for successful (GA) search. Such parameters include mutation and crossover rates in addition to population that are important issues in (GA). However, each operator of GA has a special and different influence. The impact of these factors is influenced by their probabilities; it is difficult to predefine specific ratios for each parameter, particularly, mutation and crossover operators. This paper reviews various methods for choosing mutation and crossover ratios in GAs. Next, we define new deterministic control approaches for crossover and mutation rates, namely Dynamic Decreasing of high mutation ratio/dynamic increasing of low crossover ratio (DHM/ILC), and Dynamic Increasing of Low Mutation/Dynamic Decreasing of High Crossover (ILM/DHC). The dynamic nature of the proposed methods allows the ratios of both crossover and mutation operators to be changed linearly during the search progress, where (DHM/ILC) starts with 100% ratio for mutations, and 0% for crossovers. Both mutation and crossover ratios start to decrease and increase, respectively. By the end of the search process, the ratios will be 0% for mutations and 100% for crossovers. (ILM/DHC) worked the same but the other way around. The proposed approach was compared with two parameters tuning methods (predefined), namely fifty-fifty crossover/mutation ratios, and the most common approach that uses static ratios such as (0.03) mutation rates and (0.9) crossover rates. The experiments were conducted on ten Traveling Salesman Problems (TSP). The experiments showed the effectiveness of the proposed (DHM/ILC) when dealing with small population size, while the proposed (ILM/DHC) was found to be more effective when using large population size. In fact, both proposed dynamic methods outperformed the predefined methods compared in most cases tested.

Research on the Construction Layout of Urban Sports Park Based on Constraint Graph Model

2019 ◽  
Vol 44 (3) ◽  
pp. 24-27
Author(s):  
Bai Li
Keyword(s):  
Population Size ◽  
Urban Renewal ◽  
Urban Space ◽  
Urban Culture ◽  
Graph Model ◽  
Spatial Layout ◽  
Economic Factors ◽  
Environmental Characteristics ◽  
Constraint Graph ◽  
The Impact

To study the spatial layout of urban sports parks, the constraint graph model was used to quantitatively analyze the construction of urban sports parks in China. At the same time, theories on the construction and development of urban sports parks and urban renewal at home and abroad were reviewed. The construction status of urban sports parks in China was systematically studied. Foreign case cities were investigated. Finally, the case cities in our country were discussed. The results showed that in addition to the influence of certain policies and economic factors, the development of sports parks was affected by factors such as urban space development, population size and living distribution, urban culture, regional environmental characteristics and the layout of original sports resources. Therefore, the impact of the above factors should be considered in the development of sports parks and their spatial layout. The layout of the sports park should be balanced to meet the diverse needs of the residents.

scholarly journals A logistic-harvest model with allee effect under multiplicative noise

2021 ◽  
pp. 2150044
Author(s):  
Almaz Tesfay ◽  
Daniel Tesfay ◽  
James Brannan ◽  
Jinqiao Duan
Keyword(s):  
Population Size ◽  
Carrying Capacity ◽  
Noise Intensity ◽  
Allee Effect ◽  
Large Population ◽  
Logistic Growth ◽  
Maximum Point ◽  
Harvest Rate ◽  
Harvest Model ◽  
The Impact

This work is devoted to the study of a stochastic logistic growth model with and without the Allee effect. Such a model describes the evolution of a population under environmental stochastic fluctuations and is in the form of a stochastic differential equation driven by multiplicative Gaussian noise. With the help of the associated Fokker–Planck equation, we analyze the population extinction probability and the probability of reaching a large population size before reaching a small one. We further study the impact of the harvest rate, noise intensity and the Allee effect on population evolution. The analysis and numerical experiments show that if the noise intensity and harvest rate are small, the population grows exponentially, and upon reaching the carrying capacity, the population size fluctuates around it. In the stochastic logistic-harvest model without the Allee effect, when noise intensity becomes small (or goes to zero), the stationary probability density becomes more acute and its maximum point approaches one. However, for large noise intensity and harvest rate, the population size fluctuates wildly and does not grow exponentially to the carrying capacity. So as far as biological meanings are concerned, we must catch at small values of noise intensity and harvest rate. Finally, we discuss the biological implications of our results.

scholarly journals The spatial Muller’s ratchet: surfing of deleterious mutations during range expansion

2019 ◽  
Author(s):  
Félix Foutel-Rodier ◽  
Alison Etheridge
Keyword(s):  
Population Size ◽  
Range Expansion ◽  
Allee Effect ◽  
Large Population ◽  
Small Population ◽  
Deleterious Mutations ◽  
Muller's Ratchet ◽  
Muller’S Ratchet ◽  
Expansion Load ◽  
The Impact

AbstractDuring a range expansion, deleterious mutations can “surf” on the colonisation front. The resultant decrease in fitness is known as expansion load. An Allee effect is known to reduce the loss of genetic diversity of expanding populations, by changing the nature of the expansion from “pulled” to “pushed”. We study the impact of an Allee effect on the formation of an expansion load with a new model, in which individuals have the genetic structure of a Muller’s ratchet. A key feature of Muller’s ratchet is that the population fatally accumulates deleterious mutations due to the stochastic loss of the fittest individuals, an event called a click of the ratchet. We observe fast clicks of the ratchet at the colonization front owing to small population size, followed by a slow fitness recovery due to migration of fit individuals from the bulk of the population, leading to a transient expansion load. For large population size, we are able to derive quantitative features of the expansion wave, such as the wave speed and the frequency of individuals carrying a given number of mutations. Using simulations, we show that the presence of an Allee effect reduces the rate at which clicks occur at the front, and thus reduces the expansion load.

scholarly journals Rapid increase in southern elephant seal genetic diversity after a founder event

2014 ◽  
Vol 281 (1779) ◽  
pp. 20133078 ◽  
Author(s):  
Mark de Bruyn ◽  
Malin L. Pinsky ◽  
Brenda Hall ◽  
Paul Koch ◽  
Carlo Baroni ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Growth ◽  
Population Size ◽  
Large Population ◽  
Elephant Seal ◽  
Raw Material ◽  
Southern Elephant Seal ◽  
Mirounga Leonina ◽  
Approximate Bayesian ◽  
The Impact

Genetic diversity provides the raw material for populations to respond to changing environmental conditions. The evolution of diversity within populations is based on the accumulation of mutations and their retention or loss through selection and genetic drift, while migration can also introduce new variation. However, the extent to which population growth and sustained large population size can lead to rapid and significant increases in diversity has not been widely investigated. Here, we assess this empirically by applying approximate Bayesian computation to a novel ancient DNA dataset that spans the life of a southern elephant seal ( Mirounga leonina ) population, from initial founding approximately 7000 years ago to eventual extinction within the past millennium. We find that rapid population growth and sustained large population size can explain substantial increases in population genetic diversity over a period of several hundred generations, subsequently lost when the population went to extinction. Results suggest that the impact of diversity introduced through migration was relatively minor. We thus demonstrate, by examining genetic diversity across the life of a population, that environmental change could generate the raw material for adaptive evolution over a very short evolutionary time scale through rapid establishment of a large, stable population.

scholarly journals PARAMETER VARIATION FOR LINEAR EQUATION SOLVER USING GENETIC ALGORITHM

2017 ◽  
Vol 15 (2) ◽  
pp. 42-50
Author(s):  
A M IKOTUN ◽  
A T AKINWALE ◽  
O T AROGUNDADE
Keyword(s):  
Genetic Algorithm ◽  
Linear Equation ◽  
Population Size ◽  
Linear Equations ◽  
Large Population ◽  
Small Population ◽  
Simultaneous Linear Equation ◽  
Solution Generation ◽  
Systems Of Linear Equations ◽  
Linear Equation Solver

Genetic Algorithm has been successfully applied for solving systems of Linear Equations; however the effects of varying the various Genetic Algorithms parameters on the GA systems of Linear Equations solver have not been investigated. Varying the GA parameters produces new and exciting information on the behaviour of the GA Linear Equation solver. In this paper,  a general introduction on the Genetic Algorithm, its application on finding solutions to the Systems of Linear equation as well as the effects of varying the Population size and Number of Generation is presented. The genetic algorithm simultaneous linear equation solver program was run several times using different sets of simultaneous linear equation while varying the population sizes as well as the number of generations in order to observe their effects on the solution generation. It was observed that small population size does not produce perfect solutions as fast as when large population size is used and small or large number of generations did not really have much impact on the attainment of perfect solution as much as population size. 

Te inf uence of ergonomic factors on the formation of occupational risk of health disorders of agricultural machine operators

2019 ◽  
Vol 1 (7) ◽  
pp. 400-405
Author(s):  
Tamara A. Novikova ◽  
Aleksey N. Danilov ◽  
Vladimir F. Spirin
Keyword(s):  
Physical Activity ◽  
Functional Condition ◽  
Anthropometric Data ◽  
Agricultural Machine ◽  
Machine Operators ◽  
Health Disorders ◽  
Space Layout ◽  
Combine Harvesters ◽  
High Degree ◽  
The Impact

Introduction. T e leading place in the structure of occupational morbidity of agricultural machine operators is occupied by vertebroneurological diseases, the development of which can be associated with the impact of ergonomic factors of labor activity. T e aim of the study is to assess the ergonomic factors of working conditions on mobile agricultural machinery and to identify their impact on the formation of health disorders of agricultural machine operators. Materials and methods. Complex physiological and ergonomic researches at operation of tractors and combine harvesters of old samples of domestic production including an assessment of the organization of workplaces on compliance to requirements of ergonomics and anthropometric data of workers, temporary, statodynamic, biomechanical characteristics of working poses and movements, a functional condition of machine operators (130 people aged 20–45 years with professional experience of work not less than three years) in dynamics of a work shift are carried out. Anthropometric studies were conducted among male machine operators (663 people) aged 18–59 years and with experience in the profession for more than three years. Results. The discrepancy between the size and space-layout parameters of workplaces ergonomic requirements and anthropometric data of machine operators, causing the formation of uncomfortable working positions, increasing physical activity and the severity of the labor process. A high degree of correlation between changes in the parameters of the neuromuscular system and the severity of the discrepancy between the ergonomic parameters of anthropometric characteristics of machine operators (r=0,7). T e results of the research allowed to determine the priority measures for the prevention of vertebroneurological diseases in agricultural machine operators. Conclusions. T e organization of workplaces on domestic tractors and combine harvesters of old samples does not meet the ergonomic requirements and anthropometric data of machine operators, which is the reason for the formation of an uncomfortable working posture, increased statodynamic physical activity, early development of fatigue and fatigue in the process, which can cause the development of pathological conditions of the spine and ligamentous apparatus. Ergonomic improvement of workplaces is one of the priority measures to preserve the health of agricultural machine operators.

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