scholarly journals A Multi-task Combinatorial Optimization Model Based on Genetic Algorithm and its Application in College Education Curriculum Planning

2015 ◽  
Vol 10 (8) ◽  
pp. 38
Author(s):  
Jianying Li ◽  
Zhe Zhou ◽  
Liying Wang
Keyword(s):  
Higher Education ◽  
Genetic Algorithm ◽  
Combinatorial Optimization ◽  
Optimization Model ◽  
Fitness Function ◽  
College Education ◽  
Curriculum Planning ◽  
Teaching Resources ◽  
Model Based ◽  
Combinatorial Model

Multi-task combinatorial optimization of a complex system is an important aspect of multi-task planning. To address the existing defects and limitations of the existing multi-task combinatorial optimization methods, the paper proposes a multi-task combinatorial model based on genetic algorithm. As a complex multi-task combinatorial optimization, the curriculum planning for higher education applies to itself the multi-task combinatorial model, which is based on genetic algorithm. Having fully considered such factors as teaching resources distribution, students’ intention and teachers’ intention, the paper designs a more efficient fitness function that has flexibly distributed courses and time in curriculum planning to meet the need of teaching in higher schools. Meanwhile, the paper utilizes specific cases of higher education to verify and analyze the algoritnm, and also carryies out a simulation test under the Matlab environment. The result indicates that the multi-task combinatorial optimization model based on genetic algorithm can relatively significantly optimize curriculum planning of higher education.

scholarly journals Application of the genetic algorithm to the task of compiling the curriculum

2018 ◽  
Author(s):  
V. A. Turchina ◽  
D. O. Tanasienko
Keyword(s):  
Higher Education ◽  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Necessary Conditions ◽  
Fitness Function ◽  
Educational Process ◽  
Heuristic Methods ◽  
Educational Groups ◽  
The Individual ◽  
Negative Property

One of the main tasks in organizing the educational process in higher education is the drawing up of a schedule of classes. It reflects the weekly student and faculty load. At the same time, when compiling, there are a number of necessary conditions and a number of desirable. The paper considers seven required and four desirable conditions. In this paper, one of the well-known approaches that can be used in drawing up a curriculum is consid-ered. The proposed scheme of the genetic algorithm, the result of which is to obtain an approximate solution to the problem of scheduling with the need to further improve it by other heuristic methods. To solve the problem, an island model of the genetic algorithm was selected and its advantages were considered. In the paper, the author's own structure of the individual, which includes chromosomes in the form of educational groups and genes as a lesson at a certain time, is presented and justified. The author presents his own implementations of the genetic algorithms. During the work, many variants of operators were tested, but they were rejected due to their inefficiency. The biggest problem was to maintain the consistency of information encoded in chromosomes. Also, two post-steps were added: to try to reduce the number of teacher conflict conflicts and to normalize the schedule - to remove windows from the schedule. The fitness function is calculated according to the following principles: if some desired or desired property is present in the individual, then a certain number is deducted from the individual's assessment, if there is a negative property, then a certain number is added to the assessment. Each criterion has its weight, so the size of the fine or rewards may be different. In this work, fines were charged for non-fulfillment of mandatory conditions, and rewards for fulfilling the desired

scholarly journals An Optimization Model for Environmental Ergonomics Assessment in Bioproduction of Food SMEs

2020 ◽  
Vol 27 (4) ◽  
pp. 296
Author(s):  
Mirwan Ushada ◽  
Hani Febri Mustika ◽  
Aina Musdholifah ◽  
Tsuyoshi Okayama
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Heart Rate ◽  
Artificial Neural Network ◽  
Optimization Model ◽  
Artificial Neural Network Model ◽  
Fitness Function ◽  
Research Result ◽  
Assessment System ◽  
Optimal Set

Environmental ergonomics in bioproduction of food Small Medium-sized Enterprises (SMEs) become a concern and need to be optimized. An optimization model was developed using a Genetic Algorithm (GA). The weight of an Artificial Neural Network Model was used as a fitness function for GA. The research objectives were: 1) To design an environmental ergonomic assessment system for bioproduction of Food SMEs, 2) To develop an optimization model for environmental ergonomic assessment using a Genetic Algorithm. GA is utilized to search optimal set points of environmental ergonomics based on the predicted fitness values. Each chromosome of GA represents the environmental ergonomics value. The parameters were heart rate, bioproduction temperature, distribution of bioproduction relative humidity and light intensity. The target of the optimization model was the bioproduction temperature set points. The research result indicated the model generated optimum values of environmental ergonomics parameter in bioproduction of food SMEs. The parameters could be used to provide standard workplace environment for the sustainability of food SMEs.

scholarly journals A Novel E-Commerce Negotiation Optimization Model Based on Improved Genetic Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 566-570
Author(s):  
Yang Liu
Keyword(s):  
Genetic Algorithm ◽  
Electronic Commerce ◽  
Value Creation ◽  
Optimization Model ◽  
Improved Genetic Algorithm ◽  
Model Based ◽  
Proposed Model ◽  
Business Market ◽  
Major Player ◽  
The Relationship

Electronic commerce has rapidly become a major player in the business market .This paper proposes a new electronic commerce negotiation optimization model based on improved genetic algorithm which depends on not only price, but also other factors of commodity. The proposed model illustrates the relationship between the business components required to support the e-commerce processes with the value creation factor and the controlling complexity. The experiment results show that the proposed algorithm can gain the optimal negotiation result more efficiently than other three kinds of negotiation algorithms in competitive bilateral multi-issue negotiation.

Sign in / Sign up

Export Citation Format

Share Document