Analysis Effect of Tournament Selection on Genetic Algorithm Performance in Traveling Salesman Problem (TSP)

Prayudani, Santi; Hizriadi, Ainul; Nababan, Erna Budhiarti; Suwilo, Saib

doi:10.1088/1742-6596/1566/1/012131

Cited by 9 publications

(4 citation statements)

References 1 publication

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“…One of the strategies to increase genetic diversity is the use of a selection method that, although more likely to choose elements with higher fitness, allows the choice of elements with lower fitness. One of those is the tournament method (Prayudani et al, 2020), which also has the advantage of being simple to implement. Fifteen, among the 50 elements of the population, are chosen to generate the next generation through 15 tournaments.…”

Section: Methodsmentioning

confidence: 99%

Genetic algorithm in the design of soybean silos for airflow homogenization

Petravicius

Binelo

Faoro

et al. 2023

Rev. bras. eng. agríc. ambient.

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One of the main processes used to maintain grain quality in large storage bins is aeration. An optimization model that considers the limited and discrete nature of the air inlets, in addition to the geometric characteristics of the storage bin, could produce results more easily applicable results for the design of new grain storage bins. The objective of this study was to parameterize and to apply the Darcy-Forchheimer model for simulating airflow in soybean grain mass as function of grain layer height, and develop an artificial intelligence method based on genetic algorithm for optimizing grain storage bin dimensions and air inlet configurations to obtain a more homogeneous airflow in the grain mass. The parameterization considered the effect of grain compaction and the OpenFOAM simulations showed good agreement with the experimental data. The proposed genetic algorithm was able to increase the airflow homogenization when compared to the grain storage bin used as reference.

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Section: Methodsmentioning

confidence: 99%

Genetic algorithm in the design of soybean silos for airflow homogenization

Petravicius

Binelo

Faoro

et al. 2023

Rev. bras. eng. agríc. ambient.

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“…This method determines the best individual from a group of randomly selected individuals. Then the best individual is chosen as a parent for the next generation [20].…”

Section: Evaluate Fitness Valuementioning

confidence: 99%

N-Days Tourist Route Recommender System in Yogyakarta Using Genetic Algorithm Method

Anshari,

Baizal

2023

jipi. jurnal. ilmiah. penelitian. dan. pembelajaran. informatik

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Tourism is one of the proven solutions for the Indonesian economy. Tourism in certain regions, such as Yogyakarta, can significantly affect the region's economic development, including creating new jobs, creating new business opportunities, and increasing regional income. However, for tourists from outside Yogyakarta, it requires planning a tour before traveling in Yogyakarta, especially if he wants to spend several days on a tour. Many previous studies have developed systems that can recommend tourist routes, but not within a few days of tourist visits. In this study, we propose the use of Genetic Algorithm (GA) for automatically generating optimal travel itinerary for some days visit (n-days tour route). We develop the recommender system by combining GA and the concept of Multi-Attribute Utility Theory (MAUT). This MAUT used for accommodating user needs based some criteria such as rating, cost, and time. Based on our experimental results, GA is optimal in terms of execution time and number of attractions visited in n-days visit. The average execution time obtained is 59.62%, and the average number of attractions visited obtained is 45.95%. These results show that this method can generate tourist routes efficiently.

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“…Furthermore, BT selection makes perfect sense when solving unimodal problems [20,32,96]. In addition, BT selection with replacement is better in achieving the best solution quality with low computational time [20,[96][97][98][99]. Additionally, the correspondence of BT selection in the expected ftness distribution is proven [23,32].…”

Section: Literature Reviewmentioning

confidence: 99%

An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation

et al. 2022

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Binary tournament (BT) selection is known as an established selection operator that has been employed in various problems. However, in the development of evolutionary algorithms (EA), this selection operator has a drawback in providing an efficient implementation of the union procedure, which cannot guarantee a parsimonious knowledge base with reduced number of rules. Therefore, this paper introduces binary-standard deviation (SD) tournament selection into EA as an enhancement of BT that can lead to focus on more exploration in terms of searching for the best solutions. The proposed selection operator has been experimented within fish feed formulation in grouper fish farming as a case study on finding the minimum cost and fulfilling constraints. This approach is better than experimental design in terms of costs and time. The motivation for doing so is to search for alternative ingredients for the grouper fish, as the price of trash fish is too luxurious. It is because grouper fish are carnivorous and need many trash fish for better growth. The novelty of the proposed SD tournament selection is compared with BT selection in terms of searching for an efficient but not myopic algorithm. Hence, based on the comparative study, the findings of the enhanced selection operator towards the EA have been convinced and accepted in terms of better cost and fulfilling constraints requirements.

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Analysis Effect of Tournament Selection on Genetic Algorithm Performance in Traveling Salesman Problem (TSP)

Cited by 9 publications

References 1 publication

Genetic algorithm in the design of soybean silos for airflow homogenization

Genetic algorithm in the design of soybean silos for airflow homogenization

N-Days Tourist Route Recommender System in Yogyakarta Using Genetic Algorithm Method

An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation

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